JOINT SPEECH RECOGNITION AND AUDIO CAPTIONING

Chaitanya Narisetty*, Emiru Tsunoo, Xuankai Chang, Yosuke Kashiwagi, Michael Hentschel, Shinji Watanabe

*この研究の対応する著者

研究成果: Conference contribution

1 被引用数 (Scopus)

抄録

Speech samples recorded in both indoor and outdoor environments are often contaminated with secondary audio sources. Most end-to-end monaural speech recognition systems either remove these background sounds using speech enhancement or train noise-robust models. For better model interpretability and holistic understanding, we aim to bring together the growing field of automated audio captioning (AAC) and the thoroughly studied automatic speech recognition (ASR). The goal of AAC is to generate natural language descriptions of contents in audio samples. We propose several approaches for end-to-end joint modeling of ASR and AAC tasks and demonstrate their advantages over traditional approaches, which model these tasks independently. A major hurdle in evaluating our proposed approach is the lack of labeled audio datasets with both speech transcriptions and audio captions. Therefore we also create a multi-task dataset by mixing the clean speech Wall Street Journal corpus with multiple levels of background noises chosen from the AudioCaps dataset. We also perform extensive experimental evaluation and show improvements of our proposed methods as compared to existing state-of-the-art ASR and AAC methods.

本文言語English
ホスト出版物のタイトル2022 IEEE International Conference on Acoustics, Speech, and Signal Processing, ICASSP 2022 - Proceedings
出版社Institute of Electrical and Electronics Engineers Inc.
ページ7892-7896
ページ数5
ISBN(電子版)9781665405409
DOI
出版ステータスPublished - 2022
外部発表はい
イベント47th IEEE International Conference on Acoustics, Speech, and Signal Processing, ICASSP 2022 - Virtual, Online, Singapore
継続期間: 2022 5月 232022 5月 27

出版物シリーズ

名前ICASSP, IEEE International Conference on Acoustics, Speech and Signal Processing - Proceedings
2022-May
ISSN(印刷版)1520-6149

Conference

Conference47th IEEE International Conference on Acoustics, Speech, and Signal Processing, ICASSP 2022
国/地域Singapore
CityVirtual, Online
Period22/5/2322/5/27

ASJC Scopus subject areas

  • ソフトウェア
  • 信号処理
  • 電子工学および電気工学

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