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5 months ago

SpEx+: A Complete Time Domain Speaker Extraction Network

Meng Ge; Chenglin Xu; Longbiao Wang; Eng Siong Chng; Jianwu Dang; Haizhou Li

SpEx+: A Complete Time Domain Speaker Extraction Network

Abstract

Speaker extraction aims to extract the target speech signal from a multi-talker environment given a target speaker's reference speech. We recently proposed a time-domain solution, SpEx, that avoids the phase estimation in frequency-domain approaches. Unfortunately, SpEx is not fully a time-domain solution since it performs time-domain speech encoding for speaker extraction, while taking frequency-domain speaker embedding as the reference. The size of the analysis window for time-domain and the size for frequency-domain input are also different. Such mismatch has an adverse effect on the system performance. To eliminate such mismatch, we propose a complete time-domain speaker extraction solution, that is called SpEx+. Specifically, we tie the weights of two identical speech encoder networks, one for the encoder-extractor-decoder pipeline, another as part of the speaker encoder. Experiments show that the SpEx+ achieves 0.8dB and 2.1dB SDR improvement over the state-of-the-art SpEx baseline, under different and same gender conditions on WSJ0-2mix-extr database respectively.

Benchmarks

BenchmarkMethodologyMetrics
speech-extraction-on-wsj0-2mix-extrSpEx+ (tied)
SI-SDR: 18.20

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SpEx+: A Complete Time Domain Speaker Extraction Network | Papers | HyperAI