@inproceedings{98dc257473ea44fd92944db3b2f5c88c,
title = "Motion informed audio source separation",
abstract = "In this paper we tackle the problem of single channel audio source separation driven by descriptors of the sounding object's motion. As opposed to previous approaches, motion is included as a soft-coupling constraint within the nonnegative matrix factorization framework. The proposed method is applied to a multimodal dataset of instruments in string quartet performance recordings where bow motion information is used for separation of string instruments. We show that the approach offers better source separation result than an audio-based baseline and the state-of-the-art multimodal-based approaches on these very challenging music mixtures.",
keywords = "audio source separation, motion, multimodal analysis, nonnegative matrix factorization",
author = "Sanjeel Parekh and Slim Essid and Alexey Ozerov and Duong, \{Ngoc Q.K.\} and Patrick Perez and Gael Richard",
note = "Publisher Copyright: {\textcopyright} 2017 IEEE.; 2017 IEEE International Conference on Acoustics, Speech, and Signal Processing, ICASSP 2017 ; Conference date: 05-03-2017 Through 09-03-2017",
year = "2017",
month = jun,
day = "16",
doi = "10.1109/ICASSP.2017.7951787",
language = "English",
series = "ICASSP, IEEE International Conference on Acoustics, Speech and Signal Processing - Proceedings",
publisher = "Institute of Electrical and Electronics Engineers Inc.",
pages = "6--10",
booktitle = "2017 IEEE International Conference on Acoustics, Speech, and Signal Processing, ICASSP 2017 - Proceedings",
}