TR2018-006

Speaker Adaptation for Multichannel End-to-End Speech Recognition


    •  Ochiai, T., Watanabe, S., Katagiri, S., Hori, T., Hershey, J.R., "Speaker Adaptation for Multichannel End-to-End Speech Recognition", IEEE International Conference on Acoustics, Speech, and Signal Processing (ICASSP), DOI: 10.1109/​ICASSP.2018.8462161, April 2018, pp. 6707-6711.
      BibTeX TR2018-006 PDF
      • @inproceedings{Ochiai2018apr,
      • author = {Ochiai, Tsubasa and Watanabe, Shinji and Katagiri, Shigeru and Hori, Takaaki and Hershey, John R.},
      • title = {Speaker Adaptation for Multichannel End-to-End Speech Recognition},
      • booktitle = {IEEE International Conference on Acoustics, Speech, and Signal Processing (ICASSP)},
      • year = 2018,
      • pages = {6707--6711},
      • month = apr,
      • doi = {10.1109/ICASSP.2018.8462161},
      • url = {https://www.merl.com/publications/TR2018-006}
      • }
  • Research Areas:

    Artificial Intelligence, Speech & Audio

Abstract:

Recent work on multichannel end-to-end automatic speech recognition (ASR) has shown that multichannel speech enhancement and speech recognition functions can be integrated into a deep neural network (DNN)-based system, and promising experimental results have been shown using the CHiME-4 and AMI corpora. In other recent DNN-based hidden Markov model (DNN-HMM) hybrid architectures, the effectiveness of speaker adaptation has been well established. Motivated by these results, we propose a multi-path adaptation scheme for end-to-end multichannel ASR, which combines the unprocessed noisy speech features with a speech-enhanced pathway to improve upon previous end-to-end ASR approaches. Experimental results using CHiME-4 show that (1) our proposed multi-path adaptation scheme improves ASR performance and (2) adapting the encoder network is more effective than adapting the neural beamformer, attention mechanism, or decoder network.

 

  • Related News & Events

    •  NEWS   MERL presenting 9 papers at ICASSP 2018
      Date: April 15, 2018 - April 20, 2018
      Where: Calgary, AB
      MERL Contacts: Petros T. Boufounos; Toshiaki Koike-Akino; Jonathan Le Roux; Dehong Liu; Hassan Mansour; Philip V. Orlik; Pu (Perry) Wang
      Research Areas: Computational Sensing, Digital Video, Speech & Audio
      Brief
      • MERL researchers are presenting 9 papers at the IEEE International Conference on Acoustics, Speech & Signal Processing (ICASSP), which is being held in Calgary from April 15-20, 2018. Topics to be presented include recent advances in speech recognition, audio processing, and computational sensing. MERL is also a sponsor of the conference.

        ICASSP is the flagship conference of the IEEE Signal Processing Society, and the world's largest and most comprehensive technical conference focused on the research advances and latest technological development in signal and information processing. The event attracts more than 2000 participants each year.
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  • Related Publications

  •  Ochiai, T., Watanabe, S., Hori, T., Hershey, J.R., "Multichannel End-to-end Speech Recognition", International Conference on Machine Learning (ICML), August 2017.
    BibTeX TR2017-107 PDF
    • @inproceedings{Ochiai2017aug,
    • author = {Ochiai, Tsubasa and Watanabe, Shinji and Hori, Takaaki and Hershey, John R.},
    • title = {Multichannel End-to-end Speech Recognition},
    • booktitle = {International Conference on Machine Learning (ICML)},
    • year = 2017,
    • month = aug,
    • url = {https://www.merl.com/publications/TR2017-107}
    • }
  •  Ochiai, T., Watanabe, S., Hori, T., Hershey, J.R., "Multichannel End-to-end Speech Recognition", arXiv, March 2017.
    BibTeX arXiv
    • @article{Ochiai2017mar,
    • author = {Ochiai, Tsubasa and Watanabe, Shinji and Hori, Takaaki and Hershey, John R.},
    • title = {Multichannel End-to-end Speech Recognition},
    • journal = {arXiv},
    • year = 2017,
    • month = mar,
    • url = {https://arxiv.org/abs/1703.04783}
    • }