Spotify AB patent applications on April 25th, 2024
Patent Applications by Spotify AB on April 25th, 2024
Spotify AB: 5 patent applications
Spotify AB has applied for patents in the areas of G06F16/65 (2), G06F16/683 (2), G06F16/438 (1), G06F16/432 (1), G06F16/638 (1) G06F16/65 (2), G06F16/4387 (1), G06F16/432 (1), G06F16/639 (1), G06F16/635 (1)
With keywords such as: media, user, items, item, content, simulated, respective, embeddings, generating, and audio in patent application abstracts.
Patent Applications by Spotify AB
20240134902.SYSTEMS AND METHODS FOR MEDIA PLAYLIST GENERATION_simplified_abstract_(spotify ab)
Inventor(s): Paul Lamere of Bath ME (US) for spotify ab, Zachary Damien Shaw of Arlington MA (US) for spotify ab, Aaron Paul Harmon of New York NY (US) for spotify ab, Marcus Daniel Better of Arlington MA (US) for spotify ab
IPC Code(s): G06F16/438, G06F16/432
CPC Code(s):
Abstract: the various implementations described herein include methods and devices for identifying and presenting content to users. in one aspect, a method includes providing a domain specific language (dsl) tool to a user of the computing device and receiving a plurality of user inputs via the dsl tool. the plurality of user inputs includes: an input identifying a dsl object corresponding to a media pool; an input identifying a dsl object corresponding to a mutator to be applied to the media pool; and inputs identifying a plurality of dsl objects corresponding to respective objectives for a media set list. the method also includes generating the media set list from the media pool based on the mutator and the objectives and presenting information about the generated media set list to the user.
Inventor(s): Colin Patrick Fahy of Brooklyn NY (US) for spotify ab, Leila Catherine Siddique of New York NY (US) for spotify ab, Christopher Ciollaro of Boston MA (US) for spotify ab, Matthew Budelman of Providence RI (US) for spotify ab, Mark VanMiddlesworth of Cambridge MA (US) for spotify ab, Stanislav Chekalin of Brooklyn NY (US) for spotify ab
IPC Code(s): G06F16/638, G06F16/635, G06F16/65, G06F16/683
CPC Code(s):
Abstract: 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.
20240134907.SYSTEMS AND METHODS FOR DETECTING MISMATCHED CONTENT_simplified_abstract_(spotify ab)
Inventor(s): Desi Hristova of London (GB) for spotify ab, Brian Regan of London (GB) for spotify ab, Nicola Montecchio of Berlin (DE) for spotify ab
IPC Code(s): G06F16/65, G06F16/64, G06F16/683
CPC Code(s):
Abstract: an electronic device obtains a plurality of media items, including, for each media item in the plurality, a set of attributes of the media item. the device provides the set of attributes for each media item of the plurality of media items to a machine learning model that is trained to determine a pairwise similarity between respective media items in the plurality of media items and generates an acyclic graph of an output of the machine learning model that is trained to determine pairwise similarity distances between respective media items in the plurality of media items. the device clusters nodes of the acyclic graph, each node corresponding to a media item. based on the clustering, the electronic device modifies metadata associated with a first media item in a first cluster and displays a representation of the first media item in a user interface according to the modified metadata.
20240135974.SYSTEMS AND METHODS FOR LYRICS ALIGNMENT_simplified_abstract_(spotify ab)
Inventor(s): Simon René Georges DURAND of Paris (FR) for spotify ab, Daniel STOLLER of Bonn (DE) for spotify ab
IPC Code(s): G11B27/10
CPC Code(s):
Abstract: a method includes obtaining lyrics text and audio for a media item and generating, using a first encoder, a first plurality of embeddings representing symbols that appear in the lyrics text for the media item. the method includes generating, using a second encoder, a second plurality of embeddings representing an acoustic representation of the audio for the media item. the method includes determining respective similarities between embeddings of the first plurality of embeddings and embeddings of the second plurality of embeddings and aligning the lyrics text and the audio for the media item based on the respective similarities. the method includes, while streaming the audio for the media item, providing, for display, the aligned lyrics text with the streamed audio.
Inventor(s): Joseph Cauteruccio of Boston MA (US) for spotify ab, Mehdi Ben Ayed of New York NY (US) for spotify ab, Zhenwen Dai of London (GB) for spotify ab
IPC Code(s): H04L65/1069, H04L65/613
CPC Code(s):
Abstract: simulator augmented content selection is provided by initializing a content selection object according to session initialization parameter values associated with a simulated media content playback session. the content selection object corresponds to a candidate content selection machine learning model trained to predict selectable content media items for at least one simulated user. a simulated session including a sequence of predicted simulated user next actions and one or more predicted sets of selectable content items are generated by applying a simulated user model to content items identified by the initialized content selection object, where the simulated user model is trained to predict a next action of the simulated user in response to a simulated playback input received from the simulated user and each set of the selectable content items are correlated to each next action in the sequence of predicted simulated user next actions.
