End-to-end Speech Recognition with Word-Based Rnn Language Models

Takaaki Hori, Jaejin Cho, Shinji Watanabe

研究成果: Conference contribution

11 引用 (Scopus)

抜粋

This paper investigates the impact of word-based RNN language models (RNN-LMs) on the performance of end-to-end automatic speech recognition (ASR). In our prior work, we have proposed a multi-level LM, in which character-based and word-based RNN-LMs are combined in hybrid CTC/attention-based ASR. Although this multi-level approach achieves significant error reduction in the Wall Street Journal (WSJ) task, two different LMs need to be trained and used for decoding, which increase the computational cost and memory usage. In this paper, we further propose a novel word-based RNN-LM, which allows us to decode with only the word-based LM, where it provides look-ahead word probabilities to predict next characters instead of the character-based LM, leading competitive accuracy with less computation compared to the multi-level LM. We demonstrate the efficacy of the word-based RNN-LMs using a larger corpus, LibriSpeech, in addition to WSJ we used in the prior work. Furthermore, we show that the proposed model achieves 5.1 %WER for WSJ Eval'92 test set when the vocabulary size is increased, which is the best WER reported for end-to-end ASR systems on this benchmark.

元の言語English
ホスト出版物のタイトル2018 IEEE Spoken Language Technology Workshop, SLT 2018 - Proceedings
出版者Institute of Electrical and Electronics Engineers Inc.
ページ389-396
ページ数8
ISBN(電子版)9781538643341
DOI
出版物ステータスPublished - 2019 2 11
外部発表Yes
イベント2018 IEEE Spoken Language Technology Workshop, SLT 2018 - Athens, Greece
継続期間: 2018 12 182018 12 21

出版物シリーズ

名前2018 IEEE Spoken Language Technology Workshop, SLT 2018 - Proceedings

Conference

Conference2018 IEEE Spoken Language Technology Workshop, SLT 2018
Greece
Athens
期間18/12/1818/12/21

    フィンガープリント

ASJC Scopus subject areas

  • Computer Vision and Pattern Recognition
  • Human-Computer Interaction
  • Linguistics and Language

これを引用

Hori, T., Cho, J., & Watanabe, S. (2019). End-to-end Speech Recognition with Word-Based Rnn Language Models. : 2018 IEEE Spoken Language Technology Workshop, SLT 2018 - Proceedings (pp. 389-396). [8639693] (2018 IEEE Spoken Language Technology Workshop, SLT 2018 - Proceedings). Institute of Electrical and Electronics Engineers Inc.. https://doi.org/10.1109/SLT.2018.8639693