ASR:2015-06-01 - 版本历史

Lr：/* Text Processing */

2015-06-04T07:31:54Z

‎Text Processing

Zxw：/* Speech Processing */

2015-06-03T07:33:16Z

‎Speech Processing

Lr：/* Text Processing */

2015-06-01T01:17:46Z

‎Text Processing

2015年6月1日 (一) 01:09 Lr

2015-06-01T01:09:10Z

Lr：以“==Speech Processing == === AM development === ==== Environment ==== * grid-15 often does not work * grid-14 often does not work ==== RNN AM==== * details at http:/...”为内容创建页面

2015-06-01T01:05:01Z

以“==Speech Processing == === AM development === ==== Environment ==== * grid-15 often does not work * grid-14 often does not work ==== RNN AM==== * details at http:/...”为内容创建页面

新页面

==Speech Processing ==
=== AM development ===

==== Environment ====
* grid-15 often does not work
* grid-14 often does not work

==== RNN AM====
* details at http://liuc.cslt.org/pages/rnnam.html
* Test monophone on RNN using dark-knowledge --Chao Liu
* run using wsj,MPE --Chao Liu
* run bi-directon --Chao Liu
* train RNN with dark knowledge transfer on AURORA4 --zhiyuan
:*http://cslt.riit.tsinghua.edu.cn/cgi-bin/cvss/cvss_request.pl?account=zxw&step=view_request&cvssid=383--zhiyuan

==== Mic-Array ====
* hold
* Change the prediction from fbank to spectrum features
* investigate alpha parameter in time domian and frquency domain
* ALPHA>=0, using data generated by reverber toolkit
* consider theta
* compute EER with kaldi

====RNN-DAE(Deep based Auto-Encode-RNN)====
* 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 --Yiye Lin
:* 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
* Direct using the dark-knowledge strategy to do the ivector training.
:* 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)

===Dark knowledge===
* Ensemble using 100h dataset to construct diffrernt structures -- Mengyuan
:*http://cslt.riit.tsinghua.edu.cn/cgi-bin/cvss/cvss_request.pl?account=zxw&step=view_request&cvssid=264 --Zhiyong Zhang
* adaptation English and Chinglish
:* Try to improve the chinglish performance extremly
* unsupervised training with wsj contributes to aurora4 model --Xiangyu Zeng
* test large database with AMIDA
* test hidden layer knowledge transfer--xuewei

===bilingual recognition===
* hold
:* http://cslt.riit.tsinghua.edu.cn/cgi-bin/cvss/cvss_request.pl?account=zxw&step=view_request&cvssid=359 --Zhiyuan Tang and Mengyuan

===language vector===
* train DNN with language vector--xuewei

==Text Processing==
====RNN LM====
*character-lm rnn(hold)
*lstm+rnn
:* check the lstm-rnnlm code about how to Initialize and update learning rate.(hold)

====W2V based document classification====
* make a technical report about document classification using CNN --yiqiao
* CNN adapt to resolve the low resource problem
===Translation===
*Test the performance of the similar-pair method in bilingual recognition

===Order representation ===
* modify the objective function
* sup-sampling method to solve the low frequence word
* Sort out vectors and do the experiment on objective function convergence
* test on classification task and prediction task

===binary vector===
*Finish hamming metric binary vector.
*Try to finish binary vector.
*Do test report.

===Stochastic ListNet===
*To finish writing first edition of emnlp 2015 long paper

===relation classifier===
*Tune the best model.
*Train on new wordembedding.
*Do some analysis(length of context, track the pooling.)
*Finish the draft.

===plan to do===
* combine LDA with neural network

@@ 第62行： / 第62行： @@
 ====W2V based document classification====
-* make a technical report about document classification using CNN --yiqiao(done)
+* APSP paper
 * CNN adapt to resolve the low resource problem
 ===Translation===
-*Test the performance of the similar-pair method in bilingual recognition
+* draft paper of journal
 ===Order representation ===
 * modify the objective function(hold)
 * sup-sampling method to solve the low frequence word(hold)
-* Sort out vectors and do the experiment on objective function convergence
+* journal paper
-* test on classification task and prediction task
 ===binary vector===
-*Finish hamming metric binary vector.
+* nips paper
-*Try to finish binary vector.
-*Do  test report.
-−
 ===Stochastic ListNet===
-*To finish writing first edition of emnlp 2015 long paper
+*done
 ===relation classifier===
-*Finish the draft.
+*done
 ===plan to do===
 * combine LDA with neural network

@@ 第3行： / 第3行： @@
 ==== Environment ====
-* grid-15 often does not work
+* grid-15 and grid-11 run slowly or do not work
-* grid-14 often does not work
 ==== RNN AM====
@@ 第23行： / 第22行： @@
 ====RNN-DAE(Deep based Auto-Encode-RNN)====
 * 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 --Yiye Lin
+*  DNN-based sid --Tian Lan
 :* http://cslt.riit.tsinghua.edu.cn/cgi-bin/cvss/cvss_request.pl?account=zhangzy&step=view_request&cvssid=327