Comparison of Speech Recognition Performance Between Kaldi and Google Cloud Speech API-Reference-Cited by-同舟云学术

Comparison of Speech Recognition Performance Between Kaldi and Google Cloud Speech API

Published:2018-11-11 Issue: Volume: Page:109-115
ISSN:2190-3018
Container-title:Recent Advances in Intelligent Information Hiding and Multimedia Signal Processing
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Author:

Kimura Takashi,Nose Takashi,Hirooka Shinji,Chiba Yuya,Ito Akinori

Publisher

Springer International Publishing

Link

http://link.springer.com/content/pdf/10.1007/978-3-030-03748-2_13

Reference10 articles.

1. JEIDA Noise Database. http://research.nii.ac.jp/src/en/JEIDA-NOISE.html

2. The “nnet3” setup. http://kaldi-asr.org/doc/dnn3.html

3. Baumann, T., Kennington, C., Hough, J., Schlangen, D.: Recognising conversational speech: what an incremental asr should do for a dialogue system and how to get there. In: Dialogues with Social Robots: Enablements, Analyses, and Evaluation. pp. 421–432. Springer, Singapore (2017)

4. Itou, K., Yamamoto, M., Takeda, K., Takezawa, T., Matsuoka, T., Kobayashi, T., Shikano, K., Itahashi, S.: JNAS: Japanese speech corpus for large vocabulary continuous speech recognition research. J. Acoust. Soc. Jpn. (E) 20(3), 199–206 (1999)

5. Kudo, T., Yamamoto, K., Matsumoto, Y.: Applying conditional random fields to Japanese morphological analysis. In: Proceedings of EMNLP, pp. 230–237 (2004)

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