A method and system for linking media content. An example method includes a computing system obtaining a key term from a first media-content item. Further, the method includes the computing system identifying one or more candidate matches for the obtained key term. In addition, the method includes, for at least one identified candidate match, the computing system determining whether the candidate match is a match for the key term, with the determining including (i) determining a level of similarity between the first media-content item and one or more second media-content items associated with the candidate match and (ii) using a trained machine-learning model to validate the candidate match, based on at least the determined level of similarity and a set of features characteristic of matching. Still further, the method includes, based on the validating of the candidate match, the computing system establishing a link corresponding with the match.
This disclosure is directed to an enhanced audio file generator. One aspect is a method of enhancing input speech in an input audio file, the method comprising receiving the input audio file representing the input speech, wherein the input audio file is recorded at an audio recording device, and generating an enhanced audio file by applying an audio transformation model to the input audio file, wherein applying the audio transformation model to generate the enhanced audio file comprises extracting parameters defining audio features from the input audio file, the parameters including a noise parameter defining noise in the input audio file and one or more other preset parameters respectively defining other audio features, synthesizing clean speech based on the extracted parameters including the noise parameter, wherein synthesizing the clean speech comprises transforming the noise parameter to defined value(s); and generating the enhanced audio file with the synthesized clean speech.
G10L 21/0264 - Noise filtering characterised by the type of parameter measurement, e.g. correlation techniques, zero crossing techniques or predictive techniques
G10L 25/03 - Speech or voice analysis techniques not restricted to a single one of groups characterised by the type of extracted parameters
G10L 25/30 - Speech or voice analysis techniques not restricted to a single one of groups characterised by the analysis technique using neural networks
G10L 25/51 - Speech or voice analysis techniques not restricted to a single one of groups specially adapted for particular use for comparison or discrimination
3.
Systems and Methods for Generating a Visual Summary
A method includes extracting, from a first video content item that includes a plurality of frames, a plurality of features. The method further includes segmenting the first video content item into respective shots using change-point detection of the plurality of features, including: representing the plurality of features as a one-dimensional or multi-dimensional signal over time; identifying a change from one respective shot to another respective shot based on occurrence of one or more transitional indicators of the one-dimensional or multi-dimensional signal. The first video content item is segmented into respective shots at the identified changes. The method further includes selecting, from each respective shot, a respective key frame. The method further includes generating a visual summary of the first video content item based on one or more of the respective key frames.
H04N 21/8549 - Creating video summaries, e.g. movie trailer
G06V 10/44 - Local feature extraction by analysis of parts of the pattern, e.g. by detecting edges, contours, loops, corners, strokes or intersectionsConnectivity analysis, e.g. of connected components
G06V 10/60 - Extraction of image or video features relating to illumination properties, e.g. using a reflectance or lighting model
G06V 10/762 - Arrangements for image or video recognition or understanding using pattern recognition or machine learning using clustering, e.g. of similar faces in social networks
H04N 21/845 - Structuring of content, e.g. decomposing content into time segments
4.
METHODS AND SYSTEMS FOR PROVIDING PERSONALIZED CONTENT BASED ON SHARED LISTENING SESSIONS
An electronic device receives a request, from a first device of a host user, to initiate a first shared playback session for the first device and one or more additional devices. The electronic device streams media content from a first playback queue to the first device and to the one or more additional devices, the first playback queue including one or more media content items corresponding to the first shared playback session. The electronic device determines that the first device of the host user has left the first shared playback session and, in response, maintains the first playback queue to be accessed by the one or more additional devices. After the host user has left the first shared playback session, the electronic device provides one or more media content items from the first playback queue to at least one of the one or more additional devices.
H04N 21/442 - Monitoring of processes or resources, e.g. detecting the failure of a recording device, monitoring the downstream bandwidth, the number of times a movie has been viewed or the storage space available from the internal hard disk
H04N 21/439 - Processing of audio elementary streams
H04N 21/44 - Processing of video elementary streams, e.g. splicing a video clip retrieved from local storage with an incoming video stream or rendering scenes according to encoded video stream scene graphs
H04N 21/485 - End-user interface for client configuration
H04N 21/647 - Control signaling between network components and server or clientsNetwork processes for video distribution between server and clients, e.g. controlling the quality of the video stream, by dropping packets, protecting content from unauthorised alteration within the network, monitoring of network load or bridging between two different networks, e.g. between IP and wireless
5.
Optimizing Selection of Media Content for Long Term Outcomes
Systems and methods for optimizing selection of media content for long-term outcomes are provided. Observational data including intermediate outcomes from an observation period is combined with historical data to select media content based on estimated long-term outcomes at the end of an optimization period. As time passes, the observational data is updated with more intermediate outcomes, allowing more accurate estimates of long-term outcomes to be made. In an example, a predictive model trained using the historical data uses the observational data to estimate distributions of long-term outcomes. An action selector selects samples from the distributions and selects media content based on the samples.
H04N 21/466 - Learning process for intelligent management, e.g. learning user preferences for recommending movies
G06Q 30/0242 - Determining effectiveness of advertisements
H04N 21/442 - Monitoring of processes or resources, e.g. detecting the failure of a recording device, monitoring the downstream bandwidth, the number of times a movie has been viewed or the storage space available from the internal hard disk
H04N 21/482 - End-user interface for program selection
6.
Repetitive-Motion Activity Enhancement Based Upon Media Content Selection
Systems, devices, apparatuses, components, methods, and techniques for repetitive-motion activity enhancement based upon media content selection are provided. An example media-playback device for enhancement of a repetitive-motion activity includes a media-output device that plays media content items, a plurality of media content selection engines, and a repetitive-activity enhancement mode selection engine. The plurality of media content selection engines includes a cadence-based media content selection engine and an enhancement program engine. The cadence-based media content selection engine is configured to select media content items based on a cadence associated with the repetitive-motion activity. The enhancement program engine is configured to select a media content items according to an enhancement program for the repetitive-motion activity. The repetitive-activity enhancement mode selection engine is configured to select a media content selection engine from the plurality of engines and to cause the media-output device to playback media content items selected by the selected engine.
G11B 27/15 - IndexingAddressingTiming or synchronisingMeasuring tape travel by using information not detectable on the record carrier the information being derived from movement of the record carrier, e.g. using tachometer using mechanical sensing means
G11B 27/031 - Electronic editing of digitised analogue information signals, e.g. audio or video signals
G11B 27/10 - IndexingAddressingTiming or synchronisingMeasuring tape travel
G11B 27/28 - IndexingAddressingTiming or synchronisingMeasuring tape travel by using information detectable on the record carrier by using information signals recorded by the same method as the main recording
A computer system obtains a plurality of annotated short segments of content. The computer system trains a model for summarizing longer segments of content using training data comprising the plurality of annotated short segments of content, including: (i) applying a prompt and the plurality of the annotated short segments of content to a first language model to produce a summary of the plurality of annotated short segments of content; (ii) evaluating the summary of the plurality of annotated short segments of content against predefined criteria; and (iii) applying the evaluation of the summary and the prompt to a second language model to produce an updated version of the prompt; and iteratively performing (i), (ii), and (iii) at least two times.
An example computer-implemented method includes selecting an audio segment from a middle section of an audio track and the computing system obtaining a frequency-component representation of a time window that spans (i) the selected audio segment and (ii) context audio before and/or after the selected audio segment. Further, the example method includes providing, to a trained machine-learning model, the frequency-component representation, the trained machine-learning model having been trained by training data that identifies cuepoints within frequency-component representations of audio segments within beginning and end sections of a plurality of training audio tracks, each cuepoint being a fade-in cuepoint or a fade-out cuepoint. Still further, the example method includes obtaining, from the trained machine-learning model, based on the provided frequency-component representation, a prediction that a mid-track cuepoint is present in the selected audio segment, and the computing system generating metadata for the audio track based on the prediction.
G06F 16/683 - Retrieval characterised by using metadata, e.g. metadata not derived from the content or metadata generated manually using metadata automatically derived from the content
9.
Contrastive representations of multi-dimensional, structure treatments
Example implementations include identifying, from a plurality of training examples that each include a respective first input, second input, and output, anchor, positive, and negative training examples by: applying the second inputs of the anchor, positive, and negative training examples to a mapping function to generate respective mapped inputs, determining that the mapped inputs of the anchor and positive training examples and the anchor and negative training examples differ by less than a first threshold value, determining that the outputs of the anchor and positive training examples differ by less than a second threshold value, and determining that the outputs of the anchor and negative training examples differ by more than the second threshold value; applying the first and second inputs of the anchor, positive, and negative training examples to a machine learning model to determine a contrastive loss; and updating the machine learning model based on the contrastive loss.
Example implementations include methods and systems that relate to search results and recommendations in a media content delivery system. An example method includes providing a search query to a multi-task language model associated with a media content delivery system. The method also includes providing user engagement information to the multi-task language model. The user engagement information indicates user engagement activity with the media content delivery system. The method also includes retrieving, using the multi-task language model and based on the search query, one or more candidate media items from a media item database of the media content delivery system. The method also includes identifying, using the multi-task language model and based on the user engagement information, one or more recommended media items from the media item database.
H04N 21/25 - Management operations performed by the server for facilitating the content distribution or administrating data related to end-users or client devices, e.g. end-user or client device authentication or learning user preferences for recommending movies
H04N 21/258 - Client or end-user data management, e.g. managing client capabilities, user preferences or demographics or processing of multiple end-users preferences to derive collaborative data
H04N 21/472 - End-user interface for requesting content, additional data or servicesEnd-user interface for interacting with content, e.g. for content reservation or setting reminders, for requesting event notification or for manipulating displayed content
09 - Scientific and electric apparatus and instruments
35 - Advertising and business services
38 - Telecommunications services
41 - Education, entertainment, sporting and cultural services
Goods & Services
Downloadable computer software for providing music and audio content based on algorithms; downloadable computer software for providing periodic, personalized compilations of data and activity based on algorithms related to use of music and audio content Advertising; marketing services Audio broadcasting; audio streaming; broadcasting and streaming of music; broadcasting and streaming of audio content; streaming of music and audio content via a global computer network Entertainment services, namely, providing online non-downloadable music and audio content based on algorithms; entertainment services, namely, providing information relating to music and audio content through periodic, personalized compilations of data and activity based on algorithms related to use of music and audio content; entertainment services, namely, providing online music not downloadable; entertainment services, namely, providing online non-downloadable playback of music and audio content
12.
SYSTEMS AND METHODS FOR PROVIDING SCROLLABLE FEEDS MEDIA CONTENT
While providing a currently-playing media item, a system presents a first user interface of a media-providing service that includes: a scrollable feed that includes a representation of a content item that includes an affordance for playing back a corresponding media item, and an indicator of the currently-playing media item. The system receives a first user input. In accordance with a determination that the first user input is directed to the affordance for playing back the corresponding media item, the system plays back the corresponding media item and updating the indicator of the currently-playing media item to indicate that the corresponding media item is the currently-playing media item; and in accordance with a determination the first user input is an input to preview the corresponding media item, the system previews the corresponding media item without updating the indicator of the currently-playing media item.
H04N 21/472 - End-user interface for requesting content, additional data or servicesEnd-user interface for interacting with content, e.g. for content reservation or setting reminders, for requesting event notification or for manipulating displayed content
G06F 3/0482 - Interaction with lists of selectable items, e.g. menus
Example implementations include methods and systems that relate to providing search results in a media content delivery system. An example method includes receiving a search query input via a user interface and generating, by use of a Language Model (LM), a text-based intermediate summary based on the search query input and information about one or more backend services associated with the media content delivery system. The text-based intermediate summary is indicative of a user's search intent. The method also includes generating, by use of the LM, structured instructions based at least on the text-based intermediate summary and the information about the one or more backend services. The structured instructions are processable by one or more of the backend services. The method additionally includes executing the structured instructions by way of one or more of the backend services so as to generate search results.
H04N 21/472 - End-user interface for requesting content, additional data or servicesEnd-user interface for interacting with content, e.g. for content reservation or setting reminders, for requesting event notification or for manipulating displayed content
H04N 21/482 - End-user interface for program selection
15.
SYSTEMS AND METHODS FOR PROVIDING A FEED OF MEDIA ITEMS TO A USER
A device displays a feed of media items and initiates playback of a preview of a first media item. The device detects a first swipe input directed to the feed. The first swipe input is in a first direction. In response, the device displays a representation of a second media item as the next media item. The second media item is selected for the user using a machine learning model. While the representation of the second media item is displayed, the device initiates playback of a preview of the second media item. While displaying the second media item, the device detects a second swipe input in a second direction within the scrollable feed of media items distinct from the first direction. In response, the device initiates playback of a preview of a third media item, wherein the third media item is related to the second media item.
G06F 3/0488 - Interaction techniques based on graphical user interfaces [GUI] using specific features provided by the input device, e.g. functions controlled by the rotation of a mouse with dual sensing arrangements, or of the nature of the input device, e.g. tap gestures based on pressure sensed by a digitiser using a touch-screen or digitiser, e.g. input of commands through traced gestures
16.
SYSTEMS AND METHODS FOR SWITCHING BETWEEN MEDIA CONTENT
An electronic device streams a first media item from a first set of media items curated using a first recommendation hypothesis. While streaming the first media item, the device receives a first user input. In response to the first user input, the device determines, using a heuristic applied to a plurality of sets of media items, without user intervention, a presentation order for the plurality of sets of media items, including selecting a second set of media items as a differently-curated next set of media items in the presentation order, wherein the second set of media items is curated using a second recommendation hypothesis that is different from the first recommendation hypothesis. The device streams a second media item from the second set of media items.
H04L 65/613 - Network streaming of media packets for supporting one-way streaming services, e.g. Internet radio for the control of the source by the destination
H04L 65/1089 - In-session procedures by adding mediaIn-session procedures by removing media
09 - Scientific and electric apparatus and instruments
38 - Telecommunications services
41 - Education, entertainment, sporting and cultural services
42 - Scientific, technological and industrial services, research and design
Goods & Services
(1) Downloadable computer software for enabling users to access audio books; Downloadable computer software for use in the delivery, distribution and transmission of audio books
(2) Audio books; downloadable electronic books (1) Broadcasting of audio and multimedia content over the internet; streaming of audio and multimedia content over the internet
(2) Entertainment services, namely, providing non-downloadable audio books via the internet and other communications networks
(3) Providing online non-downloadable electronic books
(4) Providing temporary use of non-downloadable computer software for enabling users to access audio books; providing temporary use of non-downloadable computer software for use in the delivery, distribution and transmission of audio books
18.
Systems and methods for predicting violative content items
An electronic device identifies a set of seed content items that correspond to violative content items. The electronic device determines, using playback histories indicating consumption of respective content items, connections between a respective content item and a first audience that has consumed the respective content item and that has consumed at least a threshold number of seed content items from the set of seed content items. The electronic device provides information corresponding to the connections as an input to a machine learning model. The electronic device receives, as an output from the machine learning model, likelihoods that respective content items are violative content items and stores a set of content items, selected using the output from the machine learning model, as candidate content items in accordance with a determination that the content item satisfies likelihood criteria.
H04N 21/454 - Content filtering, e.g. blocking advertisements
H04N 21/258 - Client or end-user data management, e.g. managing client capabilities, user preferences or demographics or processing of multiple end-users preferences to derive collaborative data
A method and system for generating synthesized speech is disclosed. The method includes receiving a request to play a sequence of media items. The sequence of media items may include a media track and a narration media item that relates to the media track. The method further comprises generating a media item identifier for the narration media item. Based on compatibility information of a media playback device, the method includes providing the media item identifier to a shortening service. The shortening service may generate a shortened media item identifier that is provided to the media playback device. The shortened media item identifier may be used by the media playback device to retrieve a synthesized speech track for the narration media item.
A system for processing voice requests includes a voice assistant manager and a plurality of voice assistants. The voice assistant manager detects a wake word in an utterance and communicates the utterance to a voice assistant of the plurality of voice assistants. In some embodiments, the voice assistant may verify the detected wake word and communicate with a cloud service, which may also verify the detected wake word and generate a response to the utterance. In some embodiments, the voice assistant manager may activate or deactivate one or more of the voice assistants.
This disclosure is directed to adjusting a playlist of media-content items. One aspect is a method comprising receiving a request to adjust a playlist comprising initial media-content items, in response to receiving the input requesting the playlist be adjusted, compiling a set of features for the playlist and selecting a strong seed media-content item from the initial media-content items as a strong seed, predicting scores for a plurality of candidate media-content items based at least in part on the set of features for the playlist and the strong seed, and interleaving a candidate media-content item of the plurality of candidate media-content items based at least in part on the scores predicted for the plurality of candidate media-content items.
G06F 16/735 - Filtering based on additional data, e.g. user or group profiles
G06F 16/783 - Retrieval characterised by using metadata, e.g. metadata not derived from the content or metadata generated manually using metadata automatically derived from the content
23.
SYSTEMS AND METHODS FOR GENERALIZED USER REPRESENTATION WITH TRANSFER LEARNING
A computing device receives an audio embedding space that includes a plurality of vectorized sets of features from a plurality of users, including a first vectorized set of features of a first user. The audio embedding space is generated using at least a first modality encoder that pre-processes features having a first feature type into the audio embedding space and a second modality encoder that pre-processes features having a second feature type into the audio embedding space. The computing device generates a generalized representation of the first user according to at least the audio embedding space. The computing device provides the generalized representation of the first user to two or more task models. Each task model is configured to be trained to perform a respective task.
The various implementations described herein include methods and devices for generating personalized playlists. In one aspect, a method includes obtaining information about recent media items presented to a user, the information including data about a respective time of day and day of week each media item was presented to the user. The method further includes grouping the recent media items into clusters based on time of day and day of week; and generating a recommendation vector using a weighted average of the clusters. The method also includes generating a playlist for the user by identifying a plurality of media items using the recommendation vector; and presenting the playlist to the user.
G06F 16/683 - Retrieval characterised by using metadata, e.g. metadata not derived from the content or metadata generated manually using metadata automatically derived from the content
A method for processing voice input is disclosed. The method may be performed by a device including a voice assistant manager and a plurality of voice assistants. In some embodiments, the method includes receiving an utterance from a user, detecting a category of the utterance, and communicating the utterance to a selected voice assistant of the plurality of voice assistants. The selected voice assistant may be associated with the detected category. In some embodiments, the selected voice assistant may generate a response to utterance, and the response may be output to the user.
A method performed by device includes transmitting, to a server system, a request message that includes an instruction requesting the server system to return an audio item selected via the device. The method includes receiving, from the server system: the audio item and a located non-static media content item that is located, by the server system, in a second storage. The non-static media content item is associated with the first audio content item. The method includes playing back the audio item and presenting the non-static media content item.
G06F 16/683 - Retrieval characterised by using metadata, e.g. metadata not derived from the content or metadata generated manually using metadata automatically derived from the content
G06F 16/48 - Retrieval characterised by using metadata, e.g. metadata not derived from the content or metadata generated manually
G06F 16/583 - Retrieval characterised by using metadata, e.g. metadata not derived from the content or metadata generated manually using metadata automatically derived from the content
G06F 16/783 - Retrieval characterised by using metadata, e.g. metadata not derived from the content or metadata generated manually using metadata automatically derived from the content
H04N 21/431 - Generation of visual interfacesContent or additional data rendering
H04N 21/4722 - End-user interface for requesting content, additional data or servicesEnd-user interface for interacting with content, e.g. for content reservation or setting reminders, for requesting event notification or for manipulating displayed content for requesting additional data associated with the content
09 - Scientific and electric apparatus and instruments
41 - Education, entertainment, sporting and cultural services
Goods & Services
(1) Downloadable podcasts in the fields of science, technology and entertainment (1) Entertainment services, namely, providing podcasts in the fields of science, technology and entertainment; entertainment services, namely, providing a multimedia program series in the fields of science, technology and entertainment distributed via various platforms across multiple forms of transmission media
29.
Display screen or portion thereof with animated graphical user interface
A method includes, while a first user associated with a first user device is participating in a first shared playback session and a second user associated with a second user device is not participating in the first shared playback session: detecting one or more of (i) a first shake movement of the first user device or (ii) a second shake movement of the second user device. The method includes, in accordance with a first determination that the first shake movement is detected within a threshold time period of detecting the second shake movement, adding the second user to the first shared playback session; and in accordance with a second determination that the first shake movement is not detected within the threshold time period, forgoing adding the second user to the first shared playback session.
G06F 3/01 - Input arrangements or combined input and output arrangements for interaction between user and computer
G06F 3/0346 - Pointing devices displaced or positioned by the userAccessories therefor with detection of the device orientation or free movement in a 3D space, e.g. 3D mice, 6-DOF [six degrees of freedom] pointers using gyroscopes, accelerometers or tilt-sensors
H04N 21/43 - Processing of content or additional data, e.g. demultiplexing additional data from a digital video streamElementary client operations, e.g. monitoring of home network or synchronizing decoder's clockClient middleware
Example implementations include dividing a textual transcript of digital audio content into a sequence of chunks, where the chunks are chronologically non-overlapping; determining annotations for each of the chunks, the annotations including at least one of: a title of the digital audio content, a description of the digital audio content, or one or more inferred segment titles of one or more previous segments of the digital audio content; providing, to a natural language model, a first chunk from the sequence of chunks, an associated annotation, and instructions to identify: a segment found in the first chunk, and a segment title of the segment; receiving, from the natural language model, an indication of the segment and the segment title; and storing the indication of the segment and the segment title as metadata associated with the digital audio content.
A computer system displays or otherwise provides a user interface for browsing a plurality of video content items. The computer system detects an user input selecting a representation of an audio item that is associated with a video content item displayed in the user interface and in response to the user input, displays or otherwise provides, a user interface for the audio item and ceases display of the video content item.
An example method includes receiving a request to identify a set of media items for playback to a user. The method further includes providing information about the request to a diffusion model (DM) component and receiving, from the DM component, a set of vectors corresponding to the information about the request. The method also includes selecting, using a different component, a set of media items based on the set of vectors, and presenting information about the set of media items to the user.
09 - Scientific and electric apparatus and instruments
38 - Telecommunications services
41 - Education, entertainment, sporting and cultural services
42 - Scientific, technological and industrial services, research and design
Goods & Services
Downloadable computer software for enabling users to access audio books; Downloadable computer software for use in the delivery, distribution and transmission of audio books Broadcasting of audio and multimedia content over the internet; streaming of audio and multimedia content over the internet Entertainment services, namely, providing non-downloadable audio books via the internet and other communications networks Providing temporary use of non-downloadable computer software for enabling users to access audio books; providing temporary use of non-downloadable computer software for use in the delivery, distribution and transmission of audio books
09 - Scientific and electric apparatus and instruments
16 - Paper, cardboard and goods made from these materials
25 - Clothing; footwear; headgear
38 - Telecommunications services
41 - Education, entertainment, sporting and cultural services
42 - Scientific, technological and industrial services, research and design
Goods & Services
Downloadable software for providing periodic, personalized
compilations of data and activity related to use of audio
and video content; downloadable computer software for
streaming, delivering, distributing, transmitting, sharing,
storing, collecting, retrieving, organizing, creating,
recording, producing, publishing, arranging, and editing
audio, video, and multimedia content; downloadable music
files. Printed publications, namely, articles in the field of music
and entertainment; printed publications, namely, articles
with personalized compilations of data and activity related
to use of audio and video content. Clothing and apparel, namely, shirts, sweatshirts, and
jackets; headwear, namely, hats. Streaming of audio and video content via electronic
communication networks, local and global computer networks
and wireless communication networks; streaming of music to
users online via a communication network; Internet
broadcasting services; information, consultancy and advisory
services relating to the aforesaid services. Providing periodic music and entertainment information in
the field of personalized compilations of data and activity
related to use of audio and video content; providing online
newsletters in the fields of music, podcasting and audio and
video content; providing non-downloadable customized music
playlists via the internet and other communications
networks; provision of information relating to music;
providing online non-downloadable musical sound recordings;
selecting non-downloadable music recordings to create
musical playlists for others and publishing those musical
playlists; providing non-downloadable pre-recorded musical
playlists via a global computer network; information,
consultancy and advisory services relating to the aforesaid
services. Providing temporary use of non-downloadable software that
enables users to save their musical preferences for future
music play; providing temporary use of non-downloadable
software that enables users to create and save on-line
collections of their favorite music and audio-video content
for future playing.
36.
Display screen with animated graphical user interface
A server performs a method of controlling manipulation of a queue of media items to be played. The method includes displaying the queue of media items in a user interface of the first electronic device, wherein the queue of media items is generated based on a set of media preferences associated with the first electronic device. The method includes receiving, from a server system, authorization to collaboratively manipulate the queue of media items with a second electronic device associated with a second user account that is different from the first user account. The method includes after receiving authorization to collaboratively manipulate the queue of media items with the second electronic device: receiving, from the server system, an update to the queue of media items based on a request from the second electronic device; and displaying the updated queue of media items.
H04L 67/52 - Network services specially adapted for the location of the user terminal
H04W 4/02 - Services making use of location information
H04W 4/80 - Services using short range communication, e.g. near-field communication [NFC], radio-frequency identification [RFID] or low energy communication
Systems and methods for optimizing selection of media content for long-term outcomes are provided. Observational data including intermediate outcomes from an observation period is combined with historical data to select media content based on estimated long-term outcomes at the end of an optimization period. As time passes, the observational data is updated with more intermediate outcomes, allowing more accurate estimates of long-term outcomes to be made. In an example, a predictive model trained using the historical data uses the observational data to estimate distributions of long-term outcomes. An action selector selects samples from the distributions and selects media content based on the samples.
H04N 21/466 - Learning process for intelligent management, e.g. learning user preferences for recommending movies
G06Q 30/0242 - Determining effectiveness of advertisements
H04N 21/442 - Monitoring of processes or resources, e.g. detecting the failure of a recording device, monitoring the downstream bandwidth, the number of times a movie has been viewed or the storage space available from the internal hard disk
H04N 21/482 - End-user interface for program selection
A second wake word detector, at a media-playback device, that plays audio (or other) content to a device, such as a voice-enabled device, detects false wake words in the audio content. The second wake word detector analyzes the audio stream to determine if the audio stream contains any audio that sounds like the wake word. If so, the second wake word detector can generate one of a plurality of instructions that describes the time period, within the audio content, in which the false wake word was encountered. The instruction can cause a first wake word detector to assume one of a plurality of configurations. The media-playback device can then instruct or inform the voice-enabled device of the presence of the false wake word. In this way, the wake word detector, at the voice-enabled device, is not activated to receive the false wake word or ignores the wake word.
A computer trains a plurality of machine learning models, each corresponding to a subset of the listenership of a media providing service. The training includes retrieving training data comprising text and corresponding to the subset of the listenership; using the training data, training the machine learning model; retrieving a second training data comprising second texts and classifications indicating whether the second texts meet moderation criteria; and using the second training data to train the machine learning model to indicate whether text meets the moderation criteria and to provide an explanation of why the machine learning model does or does not meet the moderation criteria. The computer system provides a media content item to each machine learning model and displays a predicted likelihood of the media content item meeting the one or more moderation criteria and an explanation of the predicted likelihood.
An audio cancellation system includes a voice enabled computing system that is connected to an audio output device using a wired or wireless communication network. The voice enabled computing device can provide media content to a user and receive a voice command from the user. The connection between the voice enabled computing system and the audio output device introduces a time delay between the media content being generated at the voice enabled computing device and the media content being reproduced at the audio output device. The system operates to determine a calibration value adapted for the voice enabled computing system and the audio output device. The system uses the calibration value to filter the user's voice command from a recording of ambient sound including the media content, without requiring significant use of memory and computing resources.
G10L 15/20 - Speech recognition techniques specially adapted for robustness in adverse environments, e.g. in noise or of stress induced speech
G10L 15/22 - Procedures used during a speech recognition process, e.g. man-machine dialog
G10L 25/51 - Speech or voice analysis techniques not restricted to a single one of groups specially adapted for particular use for comparison or discrimination
A method includes receiving one or more characteristics of a listening session. The method further includes selecting, via a selection process, a first time, relative to an end of a first media content item, for requesting a second media content item based on the one or more characteristics of the listening session, wherein the first time is selected so as to provide sufficient time, with a predefined probability, for retrieving the second media content item. The method includes, while providing the first media content item, at the first time within the first media content item, transmitting a request, to a server system, for the second media content item. The method includes retrieving, from the server system, the second media content item.
H04L 65/1089 - In-session procedures by adding mediaIn-session procedures by removing media
H04L 65/613 - Network streaming of media packets for supporting one-way streaming services, e.g. Internet radio for the control of the source by the destination
Systems, devices, apparatuses, components, methods, and techniques for media a simple user interface that can facilitate discovery of contextually relevant media content with minimal navigation are provided. For example, the disclosed user interface may present contextually relevant categories, sub-categories and media content items while concurrently playing a media content item predicted to likely be selected by the user.
H04N 21/442 - Monitoring of processes or resources, e.g. detecting the failure of a recording device, monitoring the downstream bandwidth, the number of times a movie has been viewed or the storage space available from the internal hard disk
H04N 21/2668 - Creating a channel for a dedicated end-user group, e.g. by inserting targeted commercials into a video stream based on end-user profiles
H04N 21/45 - Management operations performed by the client for facilitating the reception of or the interaction with the content or administrating data related to the end-user or to the client device itself, e.g. learning user preferences for recommending movies or resolving scheduling conflicts
H04N 21/472 - End-user interface for requesting content, additional data or servicesEnd-user interface for interacting with content, e.g. for content reservation or setting reminders, for requesting event notification or for manipulating displayed content
45.
SYSTEMS AND METHODS FOR GENERATING TRAILERS (SUMMARIES) FOR AUDIO CONTENT USING A SHORT ROLLING TIME WINDOW
An electronic device receives an audio file and divides the audio file into a plurality of segments of audio. The electronic device automatically, without user input, determines, for each respective segment of audio, a descriptor from a plurality of descriptors and a value of the descriptor for the segment. The electronic device selects one or more segments of audio, less than all, of the plurality of segments of audio, based on a comparison of the respective values of respective descriptors for respective segments and genre-specific criteria selected based on a genre of the audio file. The electronic device generates a summarized version of the audio file by arranging the selected one or more segments of audio into a sequence of the one or more segments.
G10L 25/63 - Speech or voice analysis techniques not restricted to a single one of groups specially adapted for particular use for comparison or discrimination for estimating an emotional state
G10L 15/22 - Procedures used during a speech recognition process, e.g. man-machine dialog
G10L 25/30 - Speech or voice analysis techniques not restricted to a single one of groups characterised by the analysis technique using neural networks
46.
SYSTEMS AND METHODS FOR DONOR SELECTION FOR SYNTHETIC CONTROL MODELS
Systems and methods for donor selection for synthetic control models are provided. When selecting donors for synthetic control models, it is important that the selected donors are not impacted by an intervention. To determine whether potential donors are impacted by the intervention, expected post-intervention values for each donor are determined based on data from before the intervention. The expected values are compared against actual values, and training donors are selected based on the comparisons. A synthetic control model can be trained using the selected training donors.
An electronic device associated with a media-providing service stores, in a vector space, a plurality of respective vector representations for respective media content items. The electronic device receives a user input, including a text string. The electronic device generates, using a neural network, a structured query based on the text string. The electronic device determines, based on the structured query, whether to generate a vector representation of a portion of the text string. When the electronic device determines to generate the vector representation of the portion of the text string, it generates the vector representation of the portion of the text string, wherein the vector representation is embedded in the vector space, and identifies a set of media items using the vector representation of the portion of the text string. And the electronic device provides one or more select media items from the set of media items to a user.
09 - Scientific and electric apparatus and instruments
41 - Education, entertainment, sporting and cultural services
Goods & Services
Downloadable podcasts in the fields of science, technology and entertainment Entertainment services, namely, providing podcasts in the fields of science, technology and entertainment; entertainment services, namely, providing a multimedia program series in the fields of science, technology and entertainment distributed via various platforms across multiple forms of transmission media
50.
SYSTEMS AND METHODS FOR GENERATING MEDIA CONTENT RECOMMENDATIONS FOR SHARED PLAYBACK
A computer system receives, while a first user is participating in a shared playback session that includes the first user and a plurality of users other than the first user, a request for a set of recommended media items. In response to receiving the request, the computer system: retrieves a first set of media items from a playback history of the first user; retrieves a plurality of probabilistic data structures for the plurality of users other than the first user, each probabilistic data structure indicating a playback history of a respective user of the plurality of users other than the first user; and provides, for display in a user interface, the set of recommended media items that comprises a subset of the first set of media items selected based on the playback histories of the plurality of users as indicated by the plurality of probabilistic data structures.
G06F 3/0484 - Interaction techniques based on graphical user interfaces [GUI] for the control of specific functions or operations, e.g. selecting or manipulating an object, an image or a displayed text element, setting a parameter value or selecting a range
G06F 3/0482 - Interaction with lists of selectable items, e.g. menus
G06F 16/435 - Filtering based on additional data, e.g. user or group profiles
A method of providing voice feedback includes storing multiple different voice feedback recordings in at least one computer-readable storage device. The method further includes receiving a listener command corresponding to a musical selection. The method further includes determining, with a processing device, an identifying musical characteristic of the musical selection. The method further includes selecting a first voice feedback recording from the multiple different voice feedback recordings, using the processing device. The first voice feedback recording corresponds to the identifying musical characteristic. The method further includes causing playback of the first voice feedback recording and the musical selection via a media playback system.
A media content item recommendation system recommends media content items based on one or more attributes of a seed playlist. The recommended media content items can be determined from a plurality of existing playlists that have been created over a period of time. Such existing playlists can be selected based on similarity to the seed playlist.
A system for device discovery for social playback is disclosed. The system operates to connect a host media playback device to a media output device and broadcast a social playback session to guest media playback devices. Upon joining a social playback session, a guest media playback device may control the media playback at the host media playback device. Where the media output for the social playback session is provided by the media output device.
H04W 4/80 - Services using short range communication, e.g. near-field communication [NFC], radio-frequency identification [RFID] or low energy communication
Methods, systems and computer program products are provided for determining acoustic feature vectors of query and target items in a first vector space, and mapping the acoustic feature vectors to a second vector space having a lower dimension. The distribution of vectors in the second vector space can then be used to identify items from the same songs, and/or items that are complementary. A mapping function is trained using a machine learning algorithm, such that complementary audio items are closer in the second vector space than the first, according to a given distance metric.
G10L 25/51 - Speech or voice analysis techniques not restricted to a single one of groups specially adapted for particular use for comparison or discrimination
G10L 25/30 - Speech or voice analysis techniques not restricted to a single one of groups characterised by the analysis technique using neural networks
55.
Systems, Methods and Computer Program Products for Selecting Audio Filters
A training audio track feature vector is generated for training audio tracks. The training audio track feature vector includes training track vector components based on one or more feature sets. Each of the training track vector components is grouped into at least one cluster. Audio filters are mapped to one or more of the clusters, thereby building a feature-filter mapping function. Mapping functions from filters to audio output devices and/or physical space acoustic features can also be built. A media playback device receives the mapping function(s) and is enabled to apply the mapping function(s) to a query audio track feature vector to identify at least one audio filter corresponding to the query audio track. The media playback device can then apply the at least one audio filter to the query audio track.
A method includes determining a first insertion time within a first media content item; and determining a second media content item to be played at the first insertion time and/or one or more properties of the second media content item. The method includes queuing an electronic device to playback, in sequence and without user intervention: the first media content item until the first insertion time; the second media content item at the first insertion time; and the first media content item resumed after playback of the second media content item is ceased. The method includes determining one or more metrics of the second media content item, the one or more metrics selected from the group consisting of: a number of views, a number of clicks, whether playback exceeds a threshold time duration, and a number of times the second media content item is provided.
A system, method and computer product for combining audio tracks. In one example embodiment herein, the method includes determining at least one music track from a plurality of music tracks that is musically compatible with a base music track based on at least respective cosine distances between an acoustic feature vector of the base music track and an acoustic feature vector of each of the plurality of music tracks. The method includes separating the at least one music track into an accompaniment component and a vocal component. The vocal component corresponds to vocals in at least a portion of the at least one music track. The method includes adding the vocal component of the at least one music track to at least a select segment of the base music track.
Systems, methods, and devices for human-machine interfaces for utterance-based playlist selection are disclosed. In one method, a list of playlists is traversed and a portion of each is audibly output until a playlist command is received. Based on the playlist command, the traversing is stopped and a playlist is selected for playback. In examples, the list of playlists is modified based on a modification input.
Managing track deletion in a stateless playback architecture is performed by receiving a media content item deletion request requesting deletion of a targeted media content item from a list of media content items that are in queue to be played back by a plurality of participant devices in a collaborative media consumption session, creating a media content item placeholder corresponding to the targeted media content item; computing a playback position for the collaborative media consumption session based on the media content item placeholder until the media content item corresponding to the media content item placeholder has finished playing; and sending the playback position to a media playback device.
Stateless playback is performed by receiving a request from a media playback device, the request requesting a playback position associated with a collaborative media consumption session. Upon receiving the request, a playback position for the collaborative media consumption session is computed. The playback position is then communicated to the media playback device.
Stateless playback is performed by receiving a playback control instruction request from a first media playback device, the playback control instruction request requesting a playback position associated with a collaborative media consumption session to move. Upon receiving the playback control instruction request, updating a playback context. Upon receiving a request for playback instructions, an updated playback position for the collaborative media consumption session is computed. The updated playback position is then communicated to the media playback device.
H04N 21/472 - End-user interface for requesting content, additional data or servicesEnd-user interface for interacting with content, e.g. for content reservation or setting reminders, for requesting event notification or for manipulating displayed content
14 - Precious metals and their alloys; jewelry; time-keeping instruments
21 - HouseHold or kitchen utensils, containers and materials; glassware; porcelain; earthenware
25 - Clothing; footwear; headgear
41 - Education, entertainment, sporting and cultural services
Goods & Services
Jewelry; key chains; precious metals and their alloys. Water bottles; household or kitchen utensils and containers; glassware. Clothing; footwear; headgear. Entertainment services; provision of information relating to music; entertainment services, namely, providing non-downloadable playback of music in generated playlists via the internet and other communications networks; entertainment services, namely curating songs for music playlists; entertainment services, namely, music festivals and concerts; entertainment services, namely, a multimedia program series featuring music and musicians distributed via the internet and other communications networks; information, consultancy and advisory services relating to the aforesaid.
66.
Systems and methods for determining descriptors for media content items
An electronic device obtains a plurality of collections of media content items, each collection of media content items being associated with text. Based on how frequently a first media content item co-occurs with a first descriptor in text for respective collections of media items that include the first media content item, the electronic device generates, without user input, a new collection of media content items for a first user. The new collection of media content items corresponds to the first descriptor and includes the first media content item. The electronic device presents the new collection of media content items to the first user as a recommendation.
G06F 16/908 - Retrieval characterised by using metadata, e.g. metadata not derived from the content or metadata generated manually using metadata automatically derived from the content
G06F 16/68 - Retrieval characterised by using metadata, e.g. metadata not derived from the content or metadata generated manually
An electronic device provides, to a user, a user-curated playlist, the user-curated playlist including an ordered set of media items that were added by the user. While providing a first media item in the ordered set of media items, the electronic device receives a first user input selecting an option to include recommended media items in the user-curated playlist. In response to the first user input, the electronic device updates the user-curated playlist to include a first recommended media item, the first recommended media item selected without user intervention based at least in part on attributes of the user-curated playlist. The first recommended media item is positioned in the user-curated playlist in between media items that were added to the ordered set of media items by the user.
G06F 16/735 - Filtering based on additional data, e.g. user or group profiles
G06F 16/783 - Retrieval characterised by using metadata, e.g. metadata not derived from the content or metadata generated manually using metadata automatically derived from the content
68.
DEVICE CONTROL COORDINATOR FOR COLLABORATIVE MEDIA CONSUMPTION SESSIONS
Device control permissions are managed during collaborative media consumption sessions. A permissions coordinator authenticates a group of users who wish to participate in a collaborative media session. A specific set of control permissions for an initial user group. The permissions can be determined based on the number of users within that group. Permissions coordinator communicates these control permissions back to the user group.
Systems, methods, and devices for human-machine interfaces for improving machine understanding and fulfillment of utterance-based requests provided via the interfaces. Multiple candidate understandings from multiple stages of a natural language processing flow are preserved for arbitration and choosing by an arbitrator that applies arbitration rules to the plurality of candidates and chooses a single candidate for initiation of a corresponding service. In an embodiment, the arbitrator uses a media content taste profile to choose a candidate understanding for initiation of a corresponding service.
A system and method for controlling access to an on-device machine learning model without the use of encryption is described herein. For example, a request is received from an application executing on a device of a user. The request is to download a machine learning model to the device that enables a feature of the application, and the request includes information associated with the user and/or the device. The information is used to create an obfuscation key, and a derivative model can be generated using a reference copy of the machine learning model and the obfuscation key. The derivative model and the obfuscation key are then sent to the application. When the obfuscation key is provided to the derivative model at runtime, values derived from the obfuscation key are provided as additional inputs that enable the derivative model to function properly.
A method and system for generating synthesized speech is disclosed. The method includes receiving a request to play a sequence of media items. The sequence of media items may include a media track and a narration media item that relates to the media track. The method further comprises generating a media item identifier for the narration media item. Based on compatibility information of a media playback device, the method includes providing the media item identifier to a shortening service. The shortening service may generate a shortened media item identifier that is provided to the media playback device. The shortened media item identifier may be used by the media playback device to retrieve a synthesized speech track for the narration media item.
A method and system for resolving media content is disclosed. In some embodiments, the method includes requesting a manifest file for a media item identifier. The manifest file may be generated by a backend platform. The manifest file may include, among other things, a uniform resource locator (URL) that corresponds to a location of media content for the media item and a latency to generate the media content. The method further includes determining a time to request the media content from a content distribution network based at least in part on a time to play the media content and the latency time to generate the media content. The media playback device may request and play the media content.
H04N 21/8352 - Generation of protective data, e.g. certificates involving content or source identification data, e.g. UMID [Unique Material Identifier]
G10L 13/08 - Text analysis or generation of parameters for speech synthesis out of text, e.g. grapheme to phoneme translation, prosody generation or stress or intonation determination
Systems and methods for skipping to playback positions in media content using seek guides are provided. Seek guides may be associated with a media content item. Each seek guide may have a position and a radius. When a user skips to a reference position, a seek guide selector may select a seek guide to use in setting a new playback position. The seek guide selector may use a probabilistic distribution positioned based on the reference position to select a seek guide. Probabilities may be calculated for each seek guide using a cumulative distribution function, and the seek guides may be ranked based on the calculated probabilities. A seek guide may be selected based on the ranking, and a new playback position may be set based on the position of the selected seek guide.
H04N 21/472 - End-user interface for requesting content, additional data or servicesEnd-user interface for interacting with content, e.g. for content reservation or setting reminders, for requesting event notification or for manipulating displayed content
H04N 21/845 - Structuring of content, e.g. decomposing content into time segments
This disclosure is directed to systems and methods for managing a group session for consuming media content across a plurality of devices. In some configurations and by non-limiting example, the group session operates to synchronize playback and control of media content at the plurality of devices. In one aspect a method of simultaneously playing media content on a plurality of media playback devices for a group session is disclosed.
A computer system determines one or more media placement opportunities for a media application at a client device and generates a request message that includes an indication of each media placement opportunity. The request message has a hierarchical framework with a plurality of levels that includes, for each media placement opportunity: (i) a media application context level; and (ii) a sub-context level. The computer system transmits the request message to a server system; and receives, from the server system, a response to the request message that includes one or more media content items selected based on the information included in the hierarchical framework of the request message. The computer system provides, to the media application at the client device, at least one of the one or more media content items within at least one of the media placement opportunities.
H04N 21/234 - Processing of video elementary streams, e.g. splicing of video streams or manipulating encoded video stream scene graphs
H04N 21/258 - Client or end-user data management, e.g. managing client capabilities, user preferences or demographics or processing of multiple end-users preferences to derive collaborative data
A method includes retrieving a text from a database. The text corresponds to audio from a media content item that is provided by a media providing service, and the text includes a plurality of segments. The method also includes assigning a score for each segment in the text by applying the text to a trained computational model. The score corresponds to a predicted relevance of the respective segment to a narrative of the media content item. The method further includes identifying a non-narrative segment within the text using the assigned scores.
G06F 16/683 - Retrieval characterised by using metadata, e.g. metadata not derived from the content or metadata generated manually using metadata automatically derived from the content
G06F 16/635 - Filtering based on additional data, e.g. user or group profiles
A system, method and computer product for training a neural network system. The method comprises applying an audio signal to the neural network system, the audio signal including a vocal component and a non-vocal component. The method also comprises comparing an output of the neural network system to a target signal, and adjusting at least one parameter of the neural network system to reduce a result of the comparing, for training the neural network system to estimate one of the vocal component and the non-vocal component. In one example embodiment, the system comprises a U-Net architecture. After training, the system can estimate vocal or instrumental components of an audio signal, depending on which type of component the system is trained to estimate.
09 - Scientific and electric apparatus and instruments
38 - Telecommunications services
41 - Education, entertainment, sporting and cultural services
42 - Scientific, technological and industrial services, research and design
Goods & Services
Downloadable voice recognition software; downloadable computer software used to process voice commands and create audio responses to voice commands; downloadable computer software for enabling hands-free use of a mobile phone through voice recognition; downloadable speech to text conversion software; downloadable computer software for streaming, delivering, distributing, transmitting, sharing, storing, collecting, retrieving, organizing, creating, recording, producing, publishing, arranging, and editing audio, video, and multimedia content; smart speakers; audio speakers; smart home devices, namely, smart speakers for sharing data through the wireless or wired network; mobile phones; automobile accessories for audio or video, namely, audio speakers; computer hardware Voice recognition services, namely, providing internet access services through voice recognition; broadcasting of audio, video, and multimedia content over the internet; streaming of audio, video, and multimedia content over the internet Entertainment services, namely, providing non-downloadable playback of audio and video via global communications network; entertainment services, namely, compiling, publishing, and curating music playlists; entertainment services, namely, providing podcasts in the field of entertainment, music, current events, pop culture, politics, history, sports, and comedy Providing online non-downloadable computer software for voice recognition; providing online non-downloadable computer software used to process voice commands and create audio responses to voice commands; providing online non-downloadable computer software for enabling hands-free use of a mobile phone through voice recognition; providing online non-downloadable computer software for streaming, delivering, distributing, transmitting, sharing, storing, collecting, retrieving, organizing, creating, recording, producing, publishing, arranging, and editing audio, video, and multimedia content
Systems, devices, apparatuses, components, methods, and techniques for automatically generating media previews are provided. An example media system for automatically generating media previews for a particular artist include a trailer generation application configured to receive input specifying an artist and duration of a trailer, automatically select clips from two or more media items by the artist, and automatically arrange and combine the clips into a media trailer for later playback.
G06F 3/0481 - Interaction techniques based on graphical user interfaces [GUI] based on specific properties of the displayed interaction object or a metaphor-based environment, e.g. interaction with desktop elements like windows or icons, or assisted by a cursor's changing behaviour or appearance
G11B 27/022 - Electronic editing of analogue information signals, e.g. audio or video signals
H03G 3/30 - Automatic control in amplifiers having semiconductor devices
Systems and methods for snapping to seek positions in media content using seek guides are provided. Seek guides may be associated with a media content item. Each seek guide may have a position and a radius. When a user seeks to a reference position, a seek guide selector may select a seek guide to use in setting a new playback position. The seek guide selector may use a probabilistic distribution positioned based on the reference position to select a seek guide. Probabilities may be calculated for each seek guide using a cumulative distribution function, and a seek guide may be selected based on the calculated probabilities.
G06F 3/04883 - Interaction techniques based on graphical user interfaces [GUI] using specific features provided by the input device, e.g. functions controlled by the rotation of a mouse with dual sensing arrangements, or of the nature of the input device, e.g. tap gestures based on pressure sensed by a digitiser using a touch-screen or digitiser, e.g. input of commands through traced gestures for inputting data by handwriting, e.g. gesture or text
H04N 21/472 - End-user interface for requesting content, additional data or servicesEnd-user interface for interacting with content, e.g. for content reservation or setting reminders, for requesting event notification or for manipulating displayed content
H04N 21/845 - Structuring of content, e.g. decomposing content into time segments
81.
Display screen with animated graphical user interface
Systems, methods and computer products are provided for retrieving play context. Media content associated with the media content is transmitted over a network. A first media playback device broadcasts an ultrasound code to one or more second media playback devices, where the ultrasound code corresponds to a play context code. The play context code is obtained from a second media playback device and in response the second media playback device receives a play context based on the play context code.
H04N 21/4722 - End-user interface for requesting content, additional data or servicesEnd-user interface for interacting with content, e.g. for content reservation or setting reminders, for requesting event notification or for manipulating displayed content for requesting additional data associated with the content
G06F 21/16 - Program or content traceability, e.g. by watermarking
H04N 21/8358 - Generation of protective data, e.g. certificates involving watermark
A method includes receiving media content items. Using machine learning, audio segments are identified in the media content items based on analysis of content included in a corresponding media content item. Each of the identified audio segments is associated with automatically determined tags. A video clip is generated for a specific user using machine learning to automatically select, for the specific user, recommended audio segments from the identified audio segments based at least in part on prior user interactions of the specific user and the automatically determined tags of the identified audio segments, and identifying, for inclusion in the video clip, video segments of the media content items that correspond to the recommended audio segments. The video clip is provided for playback on a device associated with the specific user.
G10L 17/00 - Speaker identification or verification techniques
G10L 25/51 - Speech or voice analysis techniques not restricted to a single one of groups specially adapted for particular use for comparison or discrimination
Audio translation system includes a feature extractor and a style transfer machine learning model. The feature extractor generates for each of a plurality of source voice files one or more source voice parameters encoded as a collection of source feature vectors, and generates for each of a plurality of target voice files one or more target voice parameters encoded as a collection of target feature vectors. The style transfer machine learning model trained on the collection of source feature vectors for the plurality of source voice files and the collection of target feature vectors for the plurality of target voice files to generate a style transformed feature vector.
Systems and methods for performing bias bounded sensitivity analysis of synthetic control models are provided. Bias bounds may be determined for a synthetic control model using data from the synthetic control model. If a difference between a synthetic control determined by the synthetic control model and an observed outcome are within the bias bounds, a causal effect determined using the synthetic control model may be untrustworthy. Graphical representations may be presented based, at least in part, on the observed outcome, the synthetic control, and the bias bounds.
H04N 21/25 - Management operations performed by the server for facilitating the content distribution or administrating data related to end-users or client devices, e.g. end-user or client device authentication or learning user preferences for recommending movies
H04N 21/235 - Processing of additional data, e.g. scrambling of additional data or processing content descriptors
86.
SYSTEMS AND METHODS FOR AUTOMATICALLY ORGANIZING NARRATED MEDIA CONTENT BASED ON A MEDIA DESCRIPTION FILE
Systems and methods for automatically organizing narrated media content based on a media description file are provided. For example, a media description file may be received with narrated media content. The media description file may include information about the narrated media content, such as entitlement levels associations between narrated media content items. The narrated media content may be automatically labeled based on the media description file. A personalized user interface may be generated based on the labeled narrated media content and user subscription tiers.
H04N 21/235 - Processing of additional data, e.g. scrambling of additional data or processing content descriptors
H04N 21/239 - Interfacing the upstream path of the transmission network, e.g. prioritizing client requests
H04N 21/472 - End-user interface for requesting content, additional data or servicesEnd-user interface for interacting with content, e.g. for content reservation or setting reminders, for requesting event notification or for manipulating displayed content
87.
Systems and methods for providing scrollable feeds media content
An electronic device provides, to a user, a user-curated playlist, the user-curated playlist including an ordered set of media items that were added by the user. While providing a first media item in the ordered set of media items, the electronic device receives a first user input selecting an option to include recommended media items in the user-curated playlist. In response to the first user input, the electronic device updates the user-curated playlist to include a first recommended media item, the first recommended media item selected without user intervention based at least in part on attributes of the user-curated playlist. The first recommended media item is positioned in the user-curated playlist in between media items that were added to the ordered set of media items by the user.
H04N 21/472 - End-user interface for requesting content, additional data or servicesEnd-user interface for interacting with content, e.g. for content reservation or setting reminders, for requesting event notification or for manipulating displayed content
G06F 3/0482 - Interaction with lists of selectable items, e.g. menus
An electronic device receives a request, from a host user, to initiate a shared playback session. The electronic devices streams media from a playback queue for the shared playback session to the first device and to additional devices. The electronic device determines that the host user has left the shared playback session, and, in response, maintains the playback queue to be accessed by the additional devices. After the host user has left the shared playback session, the electronic device provides media from the playback queue to at least a second device of the additional devices. While providing the media the playback queue, the electronic device receives a request, from the second device, to leave the playback queue and, in response, provides a second media, that is not included in the playback queue, to the second device. The electronic device ceases to provide the playback queue to the second device.
H04N 21/485 - End-user interface for client configuration
H04N 21/439 - Processing of audio elementary streams
H04N 21/44 - Processing of video elementary streams, e.g. splicing a video clip retrieved from local storage with an incoming video stream or rendering scenes according to encoded video stream scene graphs
H04N 21/442 - Monitoring of processes or resources, e.g. detecting the failure of a recording device, monitoring the downstream bandwidth, the number of times a movie has been viewed or the storage space available from the internal hard disk
H04N 21/647 - Control signaling between network components and server or clientsNetwork processes for video distribution between server and clients, e.g. controlling the quality of the video stream, by dropping packets, protecting content from unauthorised alteration within the network, monitoring of network load or bridging between two different networks, e.g. between IP and wireless
89.
Systems and methods for providing user interfaces for mixed media content types
A computer system provides, from a playback queue of a plurality of audio items, a played audio item of the plurality of audio items for playback and displays representation of a video content item associated with a first audio item. In response to the first user input selecting the representation of the video content item, the computer system displays or otherwise provides a user interface for browsing a plurality of video content items. The computer system detects a second user input selecting a representation of a second audio item that is associated with a second video content item displayed in the user interface and in response to the second user input, displays or otherwise provides, a user interface for the second audio item and ceasing display of the second video content item.
Systems, methods and computer program products provide dynamic segment resolution and transfer dynamic-segment metadata across media playback devices by detecting a transfer signal indicating a playback session is to be transferred from a first media playback device to a second media playback device, where the playback session contains first dynamic-segment metadata corresponding to a first dynamic-segment having a first data format. Second dynamic-segment metadata corresponding to a second dynamic-segment having a second data format is retrieved and the second media playback device is controlled to play the second dynamic-segment using the second dynamic-segment metadata, where the first data format and the second data format are different.
A method performed by a first electronic device includes transmitting, to a server system, a first request message that includes an instruction requesting the server system to return a first audio content item selected via the first electronic device. The method includes receiving, from the server system: the first audio content item that is stored in first storage, and a located non-static media content item that is located, by the server system, in a second storage, separate and remote from the first storage. The non-static media content item associated with the first audio content item. The method includes playing back the first audio content item concurrently with presenting the non-static media content item.
G06F 16/683 - Retrieval characterised by using metadata, e.g. metadata not derived from the content or metadata generated manually using metadata automatically derived from the content
G06F 16/48 - Retrieval characterised by using metadata, e.g. metadata not derived from the content or metadata generated manually
G06F 16/583 - Retrieval characterised by using metadata, e.g. metadata not derived from the content or metadata generated manually using metadata automatically derived from the content
G06F 16/783 - Retrieval characterised by using metadata, e.g. metadata not derived from the content or metadata generated manually using metadata automatically derived from the content
H04N 21/431 - Generation of visual interfacesContent or additional data rendering
H04N 21/4722 - End-user interface for requesting content, additional data or servicesEnd-user interface for interacting with content, e.g. for content reservation or setting reminders, for requesting event notification or for manipulating displayed content for requesting additional data associated with the content
41 - Education, entertainment, sporting and cultural services
Goods & Services
Clothing; footwear; headgear; clothing and apparel, namely, shirts, sweatshirts, and jackets; headwear, namely, hats. Advertising, marketing and promotion services; advertising, marketing, and promotion services relating to live music events, musician merchandise, vinyl records, pre-recorded CDs featuring music, and audio cassettes featuring music; providing advertising space on the Internet; promotion of events; subscription to music, video, and audiovisual content transmitting and streaming services; retail services in the form of subscriptions to music, audio and multimedia content; management of personal subscriptions to music, audio and multimedia content; promotion of music, audio and multimedia content accessible on a computer software platform; providing means of purchasing access to music, video, and audiovisual content provided by transmitting and streaming services; developing and providing information on marketing programs to advertisers, marketers, and content providers; promotional services, namely, promoting the goods and services of others through online entertainment and sharing of multimedia content via the Internet and other communications networks; all of the aforesaid relating to music and playlists; none of the aforementioned services relating to the provision of a platform for facilitating online gambling or sports betting. Broadcasting; streaming; broadcasting of audio, video, and multimedia content; streaming of music, audio, images, video and other multimedia content over the internet, mobile devices, wireless networks and other computer networks and electronic communications networks; broadcasting of music and podcasts; broadcasting and transmission of streamed and downloadable digital music, audio, video and multimedia content; delivery of digital music, podcasts and audiovisual content by telecommunications services; providing online chat, email, messaging, and discussion forums where users can communicate and interact for the purposes of transmission of audio, video, audiovisual content, text, data, images, digital media, multimedia, and live-streamed content; podcasting services; podcast download services; telecommunications services, namely streaming and transmission of podcasts; audio streaming services; video streaming services; data streaming; all of the aforesaid relating to music and playlists; none of the aforementioned services relating to the provision of a platform for facilitating online gambling or sports betting. Provision of information relating to music; entertainment services, namely, providing non-downloadable playback of music in generated playlists via the internet and other communications networks; entertainment services, namely curating songs for music playlists; entertainment services, namely, music festivals and concerts; entertainment services, namely, a multimedia program series featuring music and musicians distributed via the internet and other communications networks; information, consultancy and advisory services relating to the aforesaid; none of the aforementioned services relating to the provision of a platform for facilitating online gambling or sports betting.
41 - Education, entertainment, sporting and cultural services
Goods & Services
Clothing; footwear; headgear; clothing and apparel, namely, shirts, sweatshirts, and jackets; headwear, namely, hats. Advertising, marketing and promotion services; advertising, marketing, and promotion services relating to live music events, musician merchandise, vinyl records, pre-recorded CDs featuring music, and audio cassettes featuring music; providing advertising space on the Internet; promotion of events; subscription to music, video, and audiovisual content transmitting and streaming services; retail services in the form of subscriptions to music, audio and multimedia content; management of personal subscriptions to music, audio and multimedia content; promotion of music, audio and multimedia content accessible on a computer software platform; providing means of purchasing access to music, video, and audiovisual content provided by transmitting and streaming services; developing and providing information on marketing programs to advertisers, marketers, and content providers; promotional services, namely, promoting the goods and services of others through online entertainment and sharing of multimedia content via the Internet and other communications networks. Broadcasting; streaming; broadcasting of audio, video, and multimedia content; streaming of music, audio, images, video and other multimedia content over the internet, mobile devices, wireless networks and other computer networks and electronic communications networks; broadcasting of music and podcasts; broadcasting and transmission of streamed and downloadable digital music, audio, video and multimedia content; delivery of digital music, podcasts and audiovisual content by telecommunications services; providing online chat, email, messaging, and discussion forums where users can communicate and interact for the purposes of transmission of audio, video, audiovisual content, text, data, images, digital media, multimedia, and live-streamed content; podcasting services; podcast download services; telecommunications services, namely streaming and transmission of podcasts; audio streaming services; video streaming services; data streaming. Entertainment services; provision of information relating to music; entertainment services, namely, providing non-downloadable playback of music in generated playlists via the internet and other communications networks; entertainment services, namely curating songs for music playlists; entertainment services, namely, music festivals and concerts; entertainment services, namely, a multimedia program series featuring music and musicians distributed via the internet and other communications networks; information, consultancy and advisory services relating to the aforesaid.
A method includes receiving text and inputting the received text in a prediction network. The method further includes generating, using the prediction network, speech data. The prediction network comprises a neural network that is trained to generate expressive speech data from text. The neural network is trained by: receiving a first training dataset comprising audio data and corresponding text data; acquiring a respective expressivity score for each audio sample of the audio data; selecting, from the first training dataset, a first subset of training data based on the respective expressivity scores of the audio data in the first training dataset; generating, for the first subset of training data, prediction audio data for the corresponding text data; and comparing the prediction audio data to the audio data of the first subset of training data.
G10L 25/30 - Speech or voice analysis techniques not restricted to a single one of groups characterised by the analysis technique using neural networks
G10L 25/63 - Speech or voice analysis techniques not restricted to a single one of groups specially adapted for particular use for comparison or discrimination for estimating an emotional state
96.
Systems, methods and computer program products for detecting and displaying selectable networked devices based on proximity or signal strength
An architecture is provided for displaying a list of connected devices by generating a first list of devices connected to the same local network and scanning for devices within a defined physical range of a media playback device. A second list of devices within the defined physical range is generated and compared to the first list to create a third list of devices with overlapping identifiers. The media playback device then displays the third list of devices on its interface according to proximity for the user to select an appropriate device for media playback.
A computer system associated with a media-providing service obtains a set of text descriptors from a plurality of media items in a pool of media items personalized for a first user. The system selects, from the set of text descriptors, a first text descriptor using first criteria and a second text descriptor using second criteria. The system causes an application associated with the media-providing service, executing on a client device of the first user, to concurrently display a first option for playing back a first playlist of media items associated with the first text descriptor and a second option for playing back a second playlist of media items associated with the second text descriptor. In response to receiving selection by the first user of the first option, the system provides, to the application, media items from the first playlist of media items associated with the first text descriptor.
A computer system associated with a media-providing service is provided, the media-providing service configured to provide a plurality of media items to a plurality of users of the media-providing service. The computer system is configured to perform operations for providing sets of results of media items to users based on input text provided by the users. The operations include receiving, from a user of the media-providing service, an input that includes a text string. The operations include generating, by applying the text string to a trained machine-learning model, a first set of results from the plurality of media items. The operations include retrieving, by applying the text string to a search algorithm, a second set of results being distinct from the first set of results. And the operations include providing, for playback to the user, a representation of the first set of results and the second set of results.
Systems and methods for estimating a long-term effect in the presence of unobserved confounding are provided. For example, a long-term effect of a change in user interface of a media playback application may be estimated. An experimental dataset and an observational dataset may be compiled using data from a plurality of computing devices. The observational dataset may include unobserved confounding. Using the experimental dataset, a short-term effect may be determined. Using the short-term effect and samples from the observational dataset, an instrumental variable may be computed that may be used in instrumental variable regression to estimate the long-term effect.
A system for device discovery for social playback is disclosed. The system operates to connect a host media playback device to a media output device and broadcast a social playback session to guest media playback devices. Upon joining a social playback session, a guest media playback device may control the media playback at the host media playback device. Where the media output for the social playback session is provided by the media output device.
H04W 4/80 - Services using short range communication, e.g. near-field communication [NFC], radio-frequency identification [RFID] or low energy communication
