Spotify Ab

Tristan Jehan

Nicola Montecchio

Sten Garmark

Rahul Sen

Rachel Malia Bittner

Babar Zafar

Dariusz Dziuk

Owen Smith

Nikolaos Toumpelis

Mateo Rando

Pierre Roy

François Pachet

Juan José Bosch Vicente

Mathieu Ramona

Tahora H Nazer

Pär Mikael Bohrarper

Lars Christian Olofsson

Niklas Martin Gustavsson

Bror Simon Hofverberg

Ardit Bajraktari

Luc Succes

Minwei Gu

Hunter McCurry

Gandalf Hernandez

Miguel Pereira Durão Luís

Gustav Söderström

Miles Lennon

Michael Scibor

Frej Connoly

Ulf Karlsson

Miguel Pereira Duräo Luís

Miguel Pereira Durão Luis

Thor Kell

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.

Audio stem identification systems and methods

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.

Automatically generated media preview

Systems, devices, and methods for identifying media content using indirect qualities are provided. An example media-delivery system includes a content identification engine that applies a model associated with an indirect quality to media content items to generate indirect quality scores for the media content items, filters the media content items based on metadata associated with the media content items to generate filtered media content items, and presents at least some of the filtered media content items based on the indirect quality scores. An example media-playback device includes a search control engine that presents a search interface with a user-actuatable control for specifying a value of an indirect quality for use as a search criteria, transmits the search criteria to a media-delivery service, and receives media content items matching the search criteria from the media-delivery service, wherein the media content items are identified using a statistical model.

Identifying media content

A media system includes: a media-playback device including: a media-output device that plays media content items; and a tempo control engine to: select media content based upon suitability for a repetitive-motion activity; place each media content item from the media content into two or more pools of media content, with a first pool including media content which the user has previously indicated as being relevant, and a second pool including media content that the user has not previously indicated as being relevant; and sort the media content in each of the first pool and the second pool based upon tempo.

Search media content based upon tempo

A system for playing media content items operates to provide smooth transitions between the media content items to continuously support a user's repetitive motion activity. The system can generate crossfade data containing information for transitions between media content items. The mix-in and mix-out points for the transitions are calculated to eliminate one or more portions of media content items that have lower musical energy than a majority portion of the items, and to maintain substantially consistent and/or stable musical energy (e.g., audio power or sound power) throughout the media content items including transitions therebetween.

System for managing transitions between media content items

A playlist preview is generated to provide a preview of media content items identified by a media playlist. The playlist preview can be created by selecting all or some of the media content items in the playlist, determining preview portions of the selected media content items, and arranging the preview portions with or without a transition effect. The playlist preview can be easily shared with other users through, for example, social media sites.

Playlist preview

A media-playback device acquires a heart rate, selects a song with a first tempo, and initiates playback of the song. The song meets a set of qualification criteria and the first tempo is based on the heart rate, such as being equal to or less than the heart rate. The media-playback device also initiates playback of a binaural beat at a first frequency. Over a period of time, the binaural beat's first frequency is changed to a second frequency. Over the period of time, the first tempo can also be changed to a second tempo, where the second tempo is slower than the first tempo.

Media content system for enhancing rest

A cuepoint determination system utilizes a convolutional neural network (CNN) to determine cuepoint placements within media content items to facilitate smooth transitions between them. For example, audio content from a media content item is normalized to a plurality of beats, the beats are partitioned into temporal sections, and acoustic feature groups are extracted from each beat in one or more of the temporal sections. The acoustic feature groups include at least downbeat confidence, position in bar, peak loudness, timbre and pitch. The extracted acoustic feature groups for each beat are provided as input to the CNN on a per temporal section basis to predict whether a beat immediately following the temporal section within the media content item is a candidate for cuepoint placement. A cuepoint placement is then determined from among the candidate cuepoint placements predicted by the CNN.

Cuepoint determination system

A lyrics analyzer generates tags and explicitness indicators for a set of tracks. These tags may indicate the genre, mood, occasion, or other features of each track. The lyrics analyzer does so by generating an n-dimensional vector relating to a set of topics extracted from the lyrics and then using those vectors to train a classifier to determine whether each tag applies to each track. The lyrics analyzer may also generate playlists for a user based on a single seed song by comparing the lyrics vector or the lyrics and acoustics vectors of the seed song to other songs to select songs that closely match the seed song. Such a playlist generator may also take into account the tags generated for each track.

Spoken words analyzer

A system of playing media content items determines transitions between pairs of media content items by determining desirable locations in which transitions across the pairs of media content items occur. The system uses a plurality of track features of media content items and determines such track features of each media content item associated with each of transition point candidates, such as beat positions, of that media content item. The system determines similarity in the plurality of track features between the transition point candidates of a first media content item and the transition point candidates for a second media content item being played subsequent to the first media content item. The transition points or portions of the first and second media content items are selected from the transition point candidates for the first and second media content items based on the similarity results.

Transitions between media content items

This disclosure concerns the providing of media, and more particularly to the streaming of media. In one example embodiment of a method for streaming an audio content item to an electronic device, the method comprises: receiving a first data message comprising instructions from an electronic device to return a preview segment associated with a selected audio content item, the preview segment being a portion of the selected audio content item; retrieving said selected audio content item from a first storage; analyzing audio content of the retrieved audio content item to locate a portion of the selected audio content item to be used as the preview segment; extracting the located portion of the selected audio content item from the retrieved audio content item; and transmitting the extracted portion of the selected audio content item unencrypted to the electronic device.

Playback of an unencrypted portion of an audio stream

Methods, systems and computer program products are provided for identifying an audio stem. Audio stems (t, . . . , t) are stored on a stem database and songs (S, . . . , S) made with at least a subset of the plurality of the audio stems (t, . . . , t) are stored on a song database. At least partially composed song (S*) having a predetermined number of pre-selected stems (k) are received. In turn, a probability vector (or relevance value or ranking) is produced for each stem (t, . . . , t) to be complementary to the at least partially composed song (S*).

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.

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Brooklyn, NY, United States of America

Tristan Jehan