Spotify Ab

Sony Corporation

Mathieu Ramona

François Pachet

Tristan Jehan

Pierre Roy

Juan José Bosch Vicente

Stanislaw Gorlow

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

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*).

An electronic device comprising a processing unit arranged to determine an estimation signal (y(k)) based on an input signal (x(k)) and based on a non-stationary reference signal (s(k)).

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Paris, France

Mathieu Ramona