“ASR:2015-04-13”版本间的差异

2015年4月13日 (一) 01:23的版本

Speech Processing

AM development

Environment

• grid-11 often shut down automatically, too slow computation speed.

RNN AM

• details at http://liuc.cslt.org/pages/rnnam.html
• tuning parameters on monophone NN
• run using wsj,MPE

Mic-Array

• investigate alpha parameter in time domian and frquency domain
• ALPHA>=0

Convolutive network

• HOLD

• CNN + DNN feature fusion

RNN-DAE(Deep based Auto-Encode-RNN)

• HOLD -Zhiyong
• http://cslt.riit.tsinghua.edu.cn/cgi-bin/cvss/cvss_request.pl?account=zhangzy&step=view_request&cvssid=261

Speaker ID

• DNN-based sid --Yiye
• Decode --Yiye
• http://cslt.riit.tsinghua.edu.cn/cgi-bin/cvss/cvss_request.pl?account=zhangzy&step=view_request&cvssid=327

Ivector based ASR

• http://cslt.riit.tsinghua.edu.cn/cgi-bin/cvss/cvss_request.pl?step=view_request&cvssid=340
• Ivector dimention is smaller, performance is better
• Augument to hidden layer is better than input layer
• train on wsj(testbase dev93+evl92)

Text Processing

tag LM

• similar word extension in FST

• check the formula using Bayes and experiment
• add more test data
• test the baseline(no weight) and different weight method

RNN LM

• rnn

• code the character-lm using Theano

• lstm+rnn

• check the lstm-rnnlm code about how to Initialize and update learning rate.(hold)

W2V based doc classification

• reproducible test using English data
• Code new version spherical word vector.
• Accomplish movMF model

Translation

• v5.0 demo released

• cut the dict and use new segment-tool

Sparse NN in NLP

• prepare the ACL

• test result is ok now[1].
• find the new direction.

online learning

• data is ready.prepare the ACL paper

• finish some test.
• test the result on different time.

relation classifier

• check code and find the problem that result is different on sigmoid and tanh