Adaptive-FSN: Integrating Full-Band Extraction and Adaptive Sub-Band Encoding for Monaural Speech Enhancement

Yu Sheng Tsao, Kuan Hsun Ho, Jeih Weih Hung, Berlin Chen

研究成果: 書貢獻/報告類型會議論文篇章

摘要

An important more recent thread of speech enhancement work is to utilize fine-grinded local spectral patterns with sub-band processing that complement full-band features nicely. To extend the efficacy of sub-band spectral information, we propose Adaptive-FSN, a fully convolutional real-time speech enhancement framework, to dynamically acquire a sub-band embedding within a wide range of sub-band frequencies. We exploit an adaptive subband encoder to portray sub-band processing that encapsulates a wide range of sub-band units. Then we build this effective sub-band embedding with a Conformer-based structure and multi-view attention. As for the full-band features, we make use of the FullSubNet+ architecture with its full-band extractor to get global spectral information. Finally, a Conformer-based fusion model combines the above information sources to predict the complex ideal ratio mask (cIRM). Experimental results on the VoiceBank-DEMAND benchmark task reveal that this novel framework outperforms FullSubNet+ by promoting the quality of processed utterances and reducing the implementation complexity for faster real-time computation.

原文英語
主出版物標題2022 IEEE Spoken Language Technology Workshop, SLT 2022 - Proceedings
發行者Institute of Electrical and Electronics Engineers Inc.
頁面458-464
頁數7
ISBN(電子)9798350396904
DOIs
出版狀態已發佈 - 2023
事件2022 IEEE Spoken Language Technology Workshop, SLT 2022 - Doha, 卡塔尔
持續時間: 2023 1月 92023 1月 12

出版系列

名字2022 IEEE Spoken Language Technology Workshop, SLT 2022 - Proceedings

會議

會議2022 IEEE Spoken Language Technology Workshop, SLT 2022
國家/地區卡塔尔
城市Doha
期間2023/01/092023/01/12

ASJC Scopus subject areas

  • 電腦視覺和模式識別
  • 硬體和架構
  • 媒體技術
  • 儀器
  • 語言和語言學

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