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Speech Processing
SPE-L11.3
Lecture
Speech Separation and Extraction I: Single Channel

FILTERBANK DESIGN FOR END-TO-END SPEECH SEPARATION

Manuel Pariente

Date & Time

Thu, May 7, 2020

10:00 am – 12:00 pm

Location

On-Demand

Abstract

Single-channel speech separation has recently made great progress thanks to learned filterbanks as used in ConvTasNet. In parallel, parameterized filterbanks have been proposed for speaker recognition where only center frequencies and bandwidths are learned. In this work, we extend real-valued learned and parameterized filterbanks into complex-valued analytic filterbanks and define a set of corresponding representations and masking strategies. We evaluate these filterbanks on a newly released noisy speech separation dataset (WHAM). The results show that the proposed analytic learned filterbank consistently outperforms the real-valued filterbank of ConvTasNet. Also, we validate the use of parameterized filterbanks and show that complex-valued representations and masks are beneficial in all conditions. Finally, we show that the STFT achieves its best performance for 2 ms windows


Presenter

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Session Chair

Tomohiro Nakatani

NTT Corporation