Missing data imputation for spectral audio signals

Paris Smaragdis; Bhiksha Raj; Madhusudana Shashanka

doi:10.1109/MLSP.2009.5306194

Missing data imputation for spectral audio signals

Paris Smaragdis, Bhiksha Raj, Madhusudana Shashanka

Research output: Chapter in Book/Report/Conference proceeding › Conference contribution

Abstract

With the recent attention to audio processing in the time - frequency domain we increasingly encounter the problem of missing data. In this paper we present an approach that allows for imputing missing values in the time-frequency domain of audio signals. The presented approach is able to deal with real-world polyphonic signals by performing imputation even in the presence of complex mixtures. We show that this approach outperforms generic imputation approaches, and we present a variety of situations that highlight its utility.

Original language	English (US)
Title of host publication	Machine Learning for Signal Processing XIX - Proceedings of the 2009 IEEE Signal Processing Society Workshop, MLSP 2009
DOIs	https://doi.org/10.1109/MLSP.2009.5306194
State	Published - 2009
Externally published	Yes
Event	Machine Learning for Signal Processing XIX - 2009 IEEE Signal Processing Society Workshop, MLSP 2009 - Grenoble, France Duration: Sep 2 2009 → Sep 4 2009

Publication series

Name	Machine Learning for Signal Processing XIX - Proceedings of the 2009 IEEE Signal Processing Society Workshop, MLSP 2009

Other

Other	Machine Learning for Signal Processing XIX - 2009 IEEE Signal Processing Society Workshop, MLSP 2009
Country/Territory	France
City	Grenoble
Period	9/2/09 → 9/4/09

ASJC Scopus subject areas

Human-Computer Interaction
Signal Processing
Education

Online availability

10.1109/MLSP.2009.5306194

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Smaragdis, P., Raj, B., & Shashanka, M. (2009). Missing data imputation for spectral audio signals. In Machine Learning for Signal Processing XIX - Proceedings of the 2009 IEEE Signal Processing Society Workshop, MLSP 2009 [5306194] (Machine Learning for Signal Processing XIX - Proceedings of the 2009 IEEE Signal Processing Society Workshop, MLSP 2009). https://doi.org/10.1109/MLSP.2009.5306194

Missing data imputation for spectral audio signals. / Smaragdis, Paris; Raj, Bhiksha; Shashanka, Madhusudana.

Machine Learning for Signal Processing XIX - Proceedings of the 2009 IEEE Signal Processing Society Workshop, MLSP 2009. 2009. 5306194 (Machine Learning for Signal Processing XIX - Proceedings of the 2009 IEEE Signal Processing Society Workshop, MLSP 2009).

Research output: Chapter in Book/Report/Conference proceeding › Conference contribution

Smaragdis, P, Raj, B & Shashanka, M 2009, Missing data imputation for spectral audio signals. in Machine Learning for Signal Processing XIX - Proceedings of the 2009 IEEE Signal Processing Society Workshop, MLSP 2009., 5306194, Machine Learning for Signal Processing XIX - Proceedings of the 2009 IEEE Signal Processing Society Workshop, MLSP 2009, Machine Learning for Signal Processing XIX - 2009 IEEE Signal Processing Society Workshop, MLSP 2009, Grenoble, France, 9/2/09. https://doi.org/10.1109/MLSP.2009.5306194

Smaragdis P, Raj B, Shashanka M. Missing data imputation for spectral audio signals. In Machine Learning for Signal Processing XIX - Proceedings of the 2009 IEEE Signal Processing Society Workshop, MLSP 2009. 2009. 5306194. (Machine Learning for Signal Processing XIX - Proceedings of the 2009 IEEE Signal Processing Society Workshop, MLSP 2009). doi: 10.1109/MLSP.2009.5306194

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Missing data imputation for spectral audio signals

Abstract

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