Audio Intelligence

Audio intelligence research at Spotify is advancing the state of the art in understanding music at scale to enhance how it is created, identified and consumed. We build bridges from raw audio to description, similarity, recommendation and music creation by developing machine listening technologies and synthesis algorithms. These power the next-generation of differentiating products and experiences, blurring the line between creators and consumers. Examples of active research areas in audio intelligence include information retrieval, source separation, auto tagging, auto mixing, mashups, sound modeling, vocals characterization, and music promotion.

Latest Audio Intelligence Publications

July 2020 | IJCAI - International Joint Conference on Artificial Intelligence

Seq-U-Net: A One-Dimensional Causal U-Net for Efficient Sequence Modelling

Daniel Stoller, Mi Tian, Sebastian Ewert, and Simon Dixon

July 2020 | WCCI/IJCNN - IEEE World Congress on Computational Intelligence / International Joint Conference on Neural Networks

Using a Neural Network Codec Approximation Loss to Improve Source Separation Performance in Limited Capacity Networks

Ishwarya Ananthabhotla, Sebastian Ewert, Joseph A. Paradiso