Ensemble model for audio source separation

Built an ensemble model for audio source separation that can handle mixtures whose source domain is unknown, using a confidence measure to mediate among domain-specific models based on deep clustering. We derived a confidence measure based on the clusterability of the embedding space which approximates the separation quality without ground-truth comparison.

Alisa Liu

Undergraduate researcher at Northwestern interested in NLP and computer processing of audio & music