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Focus on the Sound around You: Monaural Target Speaker Extraction via Distance and Speaker Information (2306.16241v2)

Published 28 Jun 2023 in cs.SD and eess.AS

Abstract: Previously, Target Speaker Extraction (TSE) has yielded outstanding performance in certain application scenarios for speech enhancement and source separation. However, obtaining auxiliary speaker-related information is still challenging in noisy environments with significant reverberation. inspired by the recently proposed distance-based sound separation, we propose the near sound (NS) extractor, which leverages distance information for TSE to reliably extract speaker information without requiring previous speaker enrolment, called speaker embedding self-enroLLMent (SESE). Full- & sub-band modeling is introduced to enhance our NS-Extractor's adaptability towards environments with significant reverberation. Experimental results on several cross-datasets demonstrate the effectiveness of our improvements and the excellent performance of our proposed NS-Extractor in different application scenarios.

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Authors (9)
  1. Jiuxin Lin (5 papers)
  2. Peng Wang (832 papers)
  3. Heinrich Dinkel (29 papers)
  4. Jun Chen (374 papers)
  5. Zhiyong Wu (171 papers)
  6. Zhiyong Yan (16 papers)
  7. Yongqing Wang (29 papers)
  8. Junbo Zhang (84 papers)
  9. Yujun Wang (61 papers)
Citations (6)