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Phase recovery with Bregman divergences for audio source separation
- Source :
- IEEE International Conference on Acoustics, Speech and Signal Processing (ICASSP), IEEE International Conference on Acoustics, Speech and Signal Processing (ICASSP), Jun 2021, Toronto, Canada, ICASSP
- Publication Year :
- 2021
- Publisher :
- HAL CCSD, 2021.
-
Abstract
- International audience; Time-frequency audio source separation is usually achieved by estimating the short-time Fourier transform (STFT) magnitude of each source, and then applying a phase recovery algorithm to retrieve time-domain signals. In particular, the multiple input spectrogram inversion (MISI) algorithm has shown good performance in several recent works. This algorithm minimizes a quadratic reconstruction error between magnitude spectrograms. However, this loss does not properly account for some perceptual properties of audio, and alternative discrepancy measures such as beta-divergences have been preferred in many settings. In this paper, we propose to reformulate phase recovery in audio source separation as a minimization problem involving Bregman divergences. To optimize the resulting objective, we derive a projected gradient descent algorithm. Experiments conducted on a speech enhancement task show that this approach outperforms MISI for several alternative losses, which highlights their relevance for audio source separation applications.
- Subjects :
- FOS: Computer and information sciences
Sound (cs.SD)
Computer science
Audio source separation
Speech enhancement
projected gradient descent
Computer Science - Sound
Phase recovery
symbols.namesake
Quadratic equation
[INFO.INFO-TS]Computer Science [cs]/Signal and Image Processing
Audio and Speech Processing (eess.AS)
FOS: Electrical engineering, electronic engineering, information engineering
Source separation
Projected gradient descent
Short-time Fourier transform
audio source separation
Informatique et langage
Bregman divergences
Time–frequency analysis
Fourier transform
Computer Science::Sound
[INFO.INFO-SD]Computer Science [cs]/Sound [cs.SD]
symbols
Spectrogram
speech enhancement
Gradient descent
Algorithm
Electrical Engineering and Systems Science - Audio and Speech Processing
Subjects
Details
- Language :
- English
- Database :
- OpenAIRE
- Journal :
- IEEE International Conference on Acoustics, Speech and Signal Processing (ICASSP), IEEE International Conference on Acoustics, Speech and Signal Processing (ICASSP), Jun 2021, Toronto, Canada, ICASSP
- Accession number :
- edsair.doi.dedup.....c205767866ab2d87d1884271095485b0