“智能硬件-课程阅读2”版本间的差异

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Google
  
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Google Speech Processing from Mobile to Farfield CHiME 2016
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: Google Speech Processing from Mobile to Farfield, CHiME 2016.
  
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# Parallel training of DNNs with natural gradient and parameter averaging, ICLR Workshop 2015. [http://www.danielpovey.com Dan Povey]
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JHU
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# Long short term memory-neural computation, Neural computation 9 (8), 1735-1780, 1997. [http://ieeexplore.ieee.org/document/6795963 LSTM]
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# Karpagavalli, S., and E. Chandra. "A Review on Automatic Speech Recognition Architecture and Approaches." International Journal of Signal Processing, Image Processing and Pattern Recognition 9, no. 4 (2016): 393-404.
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: Parallel training of DNNs with natural gradient and parameter averaging, ICLR Workshop 2015. [http://www.danielpovey.com Dan Povey]
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# EESEN_ End-to-End Speech Recognition using Deep RNN Models and WFST-based Decoding, ASRU 2015.
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# Learning the Speech Front-end With Raw Waveform CLDNNs, InterSpeech 2015.
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CMU
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: EESEN: End-to-End Speech Recognition using Deep RNN Models and WFST-based Decoding, ASRU 2015.
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Google
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: Learning the Speech Front-end With Raw Waveform CLDNNs, InterSpeech 2015.

2017年1月24日 (二) 18:48的最后版本

Google

Google Speech Processing from Mobile to Farfield, CHiME 2016.

JHU

Parallel training of DNNs with natural gradient and parameter averaging, ICLR Workshop 2015. Dan Povey

CMU

EESEN: End-to-End Speech Recognition using Deep RNN Models and WFST-based Decoding, ASRU 2015.

Google

Learning the Speech Front-end With Raw Waveform CLDNNs, InterSpeech 2015.
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