“ASR:2015-03-30”版本间的差异
来自cslt Wiki
（→Speech Processing） |
|||
| （1位用户的2个中间修订版本未显示） | |||
| 第4行： | 第4行： | ||
==== Environment ==== | ==== Environment ==== | ||
* grid-11 often shut down automatically, too slow computation speed. | * grid-11 often shut down automatically, too slow computation speed. | ||
| − | + | ||
==== RNN AM==== | ==== RNN AM==== | ||
* details at http://liuc.cslt.org/pages/rnnam.html | * details at http://liuc.cslt.org/pages/rnnam.html | ||
| − | * tuning parameters on monophone NN | + | * tuning parameters on monophone NN |
| + | * run using wsj,MPE | ||
==== Mic-Array ==== | ==== Mic-Array ==== | ||
* investigate alpha parameter in time domian and frquency domain | * investigate alpha parameter in time domian and frquency domain | ||
| + | * ALPHA>=0 | ||
| − | |||
| − | |||
| − | |||
| − | |||
| − | |||
====Convolutive network==== | ====Convolutive network==== | ||
* HOLD | * HOLD | ||
:* CNN + DNN feature fusion | :* CNN + DNN feature fusion | ||
| − | |||
====RNN-DAE(Deep based Auto-Encode-RNN)==== | ====RNN-DAE(Deep based Auto-Encode-RNN)==== | ||
| 第29行： | 第25行： | ||
* http://cslt.riit.tsinghua.edu.cn/cgi-bin/cvss/cvss_request.pl?account=zhangzy&step=view_request&cvssid=261 | * http://cslt.riit.tsinghua.edu.cn/cgi-bin/cvss/cvss_request.pl?account=zhangzy&step=view_request&cvssid=261 | ||
| − | |||
| − | |||
| − | |||
| − | |||
| − | |||
| − | |||
| − | |||
| − | |||
===Speaker ID=== | ===Speaker ID=== | ||
:* DNN-based sid --Yiye | :* 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 | :* http://cslt.riit.tsinghua.edu.cn/cgi-bin/cvss/cvss_request.pl?account=zhangzy&step=view_request&cvssid=327 | ||
| 第46行： | 第35行： | ||
:* Ivector dimention is smaller, performance is better | :* Ivector dimention is smaller, performance is better | ||
:* Augument to hidden layer is better than input layer | :* Augument to hidden layer is better than input layer | ||
| − | :* | + | :* train on wsj(testbase dev93+evl92) |
==Text Processing== | ==Text Processing== | ||
===tag LM=== | ===tag LM=== | ||
* similar word extension in FST | * similar word extension in FST | ||
| − | :* check the formula using | + | :* check the formula using Bayes and experiment |
====RNN LM==== | ====RNN LM==== | ||
| 第60行： | 第49行： | ||
====W2V based doc classification==== | ====W2V based doc classification==== | ||
| − | * | + | * corpus ready |
| − | * | + | * learn some benchmark. |
| + | |||
===Translation=== | ===Translation=== | ||
* v5.0 demo released | * v5.0 demo released | ||
2015年4月1日 (三) 05:39的最后版本
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
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
- corpus ready
- learn some benchmark.
Translation
- v5.0 demo released
- cut the dict and use new segment-tool
Sparse NN in NLP
- prepare the ACL
- check the code to find the problem .
- increase the dimension
- use different test set,but the result is not good.
online learning
- data is ready.prepare the ACL paper
- prepare sougouQ data and test it using current online learning method
- baseline is not normal.
