ASR Status Report 2016-11-28

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2016年11月28日 (一) 01:31Shiying讨论 | 贡献的版本

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Date People Last Week This Week


2016.11.14 Hang Luo
Ying Shi
  • some work about kazak speech recognition
  • cnn visualization
  • paper reading
  • cnn visualization
Yixiang Chen
Lantian Li
Zhiyuan Tang
YanQing Wang

Date People Last Week This Week


2016.11.21 Hang Luo
  • Explore the language recognition models including:
  • Evaluate the model in the aspect of sentence and frame, find the accuracy is very high.
  • Minimize the language model, train it single and joint with speech model, evaluate its result.
  • Continue doing the basic explore of joint training.
  • Read paper about multi-language recognition models and others.
Ying Shi
  • fighting with kazak speech recognition system:because the huge size of HCLG.fst the decoding job always make the sever done.

There are several method I have tried

  • change the size or word list and corpus this method not worked very well
  • prune the LM .And the parameter been used to prune the LM is 2e-7 the size of LM reduce from 290M to 60M but the result about wer is very poor
  • I have upload some result about several experiment to CVSS[1]
  • there are too much private affairs about myself so the job about visualization last week has been delayed I will try my best to finish it the week



Yixiang Chen
  • Learn MFCC extraction mechanism.
  • Read kaldi computer-feature code and find how to change MFCC.
  • Frequency-weighting based feature extraction.
  • Continue replay detection (Freq-Weighting and Freq-Warping).
Lantian Li
  • Joint-training on SRE and LRE (LRE task). [2]
    • Tdnn is better than LSTM.
    • LRE is a long-term task.
  • Briefly overview Interspeech SRE-related papers.
  • CSLT-Replay detection.
    • Baseline done (Freq / Mel domain).
    • performance-driven based Freq-Weighting and Freq-Warping --> Yixiang.
  • LRE task.
  • Replay detection.
Zhiyuan Tang
  • report for Weekly Reading (a brief review of interspeech16), just prepared;
  • language scores as decoding mask (1.multiply probability, very bad; 2.add log-softmax, a little bad)
  • training with mask failed
  • training with shared layers;
  • explore single tasks.