ASR:2015-06-29

Speech Processing

AM development

RNN AM

• morpheme RNN --zhiyuan

Mic-Array

• hold
• compute EER with kaldi

====Data selection unsupervised learning

• train using aurora4 --zhiyong
• train using wsj --xuewei

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

• hold
• deliver to mengyuan

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

Speaker ID

• DNN-based sid --Lantian

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

Ivector&Dvector based ASR

• hold --Tian Lan
• Cluster the speakers to speaker-classes, then using the distance or the posterior-probability as the metric
• dark-konowlege using i-vector
• train on wsj(testbase dev93+evl92)

• --hold

Dark knowledge

• test random last output layer when train MPE --zhiyuan

language vector

• hold

Text Processing

RNN LM

• character-lm rnn(hold)
• lstm+rnn

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

Neural Based Document Classification

• (hold)

Order representation

• Nested Dropout
• modify the objective function(hold)

Balance Representation

• Find error signal

Recommendation

• Reproduce baseline.

DSSM based QA

• Reproduce baseline.