Toward growing modular deep neural networks for continuous speech recognition
Author:
Publisher
Springer Science and Business Media LLC
Subject
Artificial Intelligence,Software
Link
http://link.springer.com/article/10.1007/s00521-016-2438-x/fulltext.html
Reference56 articles.
1. Baker J, Deng L, Glass J, Khudanpur S, Lee C, Morgan N et al (2009) Research developments and directions in speech recognition and understanding, Part 1. IEEE Signal Process Mag 26(3):75–80
2. Baker J, Deng L, Khudanpur S, Lee C, Glass J, Morgan N et al (2009) Updated MINDS report on speech recognition and understanding, Part 2. IEEE Signal Process Mag 26(4):78–85
3. Dahl G, Yu D, Deng L, Acero A (2012) Context-dependent pre-trained deep neural networks for large vocabulary speech recognition. IEEE Trans Audio Speech Lang Process 20(1):30–42
4. Kapadia S, Valtchev V, Young S J (1993) MMI training for continuous phoneme recognition on the TIMIT database. In: Proceedings of ICASSP
5. Juang B-H, Hou W, Lee C-H (1997) Minimum classification error rate methods for speech recognition. IEEE Trans Audio Speech Lang Process 5(3):257–265
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