ASR:2015-08-17 - 版本历史

Lr：/* financial group */

2015-08-21T06:06:53Z

‎financial group

Zxw：/* Speech Processing */

2015-08-17T08:04:39Z

‎Speech Processing

Xingchao：/* Text Processing */

2015-08-17T02:56:00Z

‎Text Processing

Xingchao：以“==Speech Processing == === AM development === ==== Environment ==== * grid-14 is on repairation * prepare to buy a server ==== RNN AM==== hold train morpheme RN...”为内容创建页面

2015-08-17T01:28:06Z

以“==Speech Processing == === AM development === ==== Environment ==== * grid-14 is on repairation * prepare to buy a server ==== RNN AM==== *hold *train morpheme RN...”为内容创建页面

新页面

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

==== Environment ====
* grid-14 is on repairation
* prepare to buy a server

==== RNN AM====
*hold
*train morpheme RNN --zhiyuan
*train using 1400h large dataset--mengyuan
*write code to tune learning rate--zhiyong

==== Mic-Array ====
* hold
* compute EER with kaldi

====Data selection unsupervised learning
* hold
* acoustic feature based submodular using Pingan dataset --zhiyong
* write code to speed up --zhiyong

====RNN-DAE(Deep based Auto-Encode-RNN)====
* hold
* deliver to mengyuan, xuewei
:* 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

===language vector===
* hold
* train using language vector with the dataset of 1400h_CN + 100h_EN--mengyuan
:* hold
* write a paper--zhiyuan
* RNN language vector
* train as a paper--xuewei

===rectifier===
* hold
* rectifier RNN --zhiyuan

===monophone===
* hold
* triphone is tranfered to monophone--zhiyong

===multi-GPU====
* multi-stream training --Sheng Su

==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)

====RNN Rank Task====
:*Paper: RNN Rank Net.
* (hold)

====Graph RNN====
:* Entity path embeded to entity.
*(hold)

====RNN Word Segment====
:* Set bound to word segment.
* (hold)

====Seq to Seq(09-15)====
* Review papers.
* Reproduce baseline. (08-03)

====Order representation ====
* Nested Dropout
:*semi-linear --> neural based auto-encoder.
* modify the objective function(hold)
====Balance Representation====
* Find error signal

====Recommendation====
* Reproduce baseline.
:*LDA matrix dissovle.
:* LDA (Text classification & Recommendation System) --> AAAI

====RNN based QA====
*Read Source Code.
*Attention based QA.
*(hold)

====RNN Poem Process====
*Seq based BP.

===Text Group Intern Project===
====Buddhist Process====
(hold)

====RNN Poem Process====
*Done by Haichao yu & Chaoyuan zuo Mentor : Tianyi Luo.

====RNN Document Vector====
(hold)

====Image Baseline====
:*Demo Release.
:*Paper Report.
*Read CNN Paper.

===Text Intuitive Idea===
====Trace Learning====
* (Hold)
====Match RNN ====
* (Hold)

=financial group=
===tonglian platform===
* learn the platform
:* arma,ar,boosting tree is done

===strategy===
* rule optimize model
:* Adaboost method
* technology index
:* survey the current technology index
* NN
:* RNN model using Theano

===display platform===
* set up the test platform in our grid

@@ 第129行： / 第129行： @@
 ===strategy===
-* rule optimize model
+* rule optimize model (hold)
 :* Adaboost method
 * technology  index
-:* survey the current technology index
+:* survey the current technology index and test several type technology index
 * NN
 :* RNN model using Theano
-−
+*
 ===display platform===
 * set up the test platform in our grid

@@ 第7行： / 第7行： @@
 ==== RNN AM====
-*hold
+*train monophone RNN --zhiyuan
-*train morpheme RNN --zhiyuan
+*train using large dataset--mengyuan
-*train using 1400h large dataset--mengyuan
 *write code to tune learning rate--zhiyong
@@ 第50行： / 第49行： @@
 * hold
 * rectifier RNN --zhiyuan
 ===multi-GPU====

@@ 第81行： / 第81行： @@
 ====Seq to Seq(09-15)====
 * Review papers.
-* Reproduce baseline. (08-03)
+* Reproduce baseline. (08-03 <--> 08-17)
 ====Order representation ====
@@ 第87行： / 第87行： @@
 :*semi-linear --> neural based auto-encoder.
 * modify the objective function(hold)
 ====Balance Representation====
 * Find error signal
@@ 第101行： / 第102行： @@
 ====RNN Poem Process====
-*Seq based BP.
+:*Seq based BP.
 ===Text Group Intern Project===
 ====Buddhist Process====
-(hold)
+:*(hold)
 ====RNN Poem Process====
@@ 第111行： / 第113行： @@
 ====RNN Document Vector====
-(hold)
+:*(hold)
 ====Image Baseline====

ASR:2015-08-17 - 版本历史

Lr：/* financial group */

Zxw：/* Speech Processing */

Xingchao：/* Text Processing */

Xingchao：以“==Speech Processing == === AM development === ==== Environment ==== * grid-14 is on repairation * prepare to buy a server ==== RNN AM==== *hold *train morpheme RN...”为内容创建页面

Xingchao：以“==Speech Processing == === AM development === ==== Environment ==== * grid-14 is on repairation * prepare to buy a server ==== RNN AM==== hold train morpheme RN...”为内容创建页面