ASR:2015-01-26 - 版本历史

2015年1月30日 (五) 02:16 Zhangzy

2015-01-30T02:16:12Z

Lr：/* Text Processing */

2015-01-27T04:28:42Z

‎Text Processing

Lr：以“==Speech Processing == === AM development === ==== Environment ==== * May gpu760 of grid-14 be something wrong. To be exchanged. * grid-11 often shutdown automatica...”为内容创建页面

2015-01-27T04:15:04Z

以“==Speech Processing == === AM development === ==== Environment ==== * May gpu760 of grid-14 be something wrong. To be exchanged. * grid-11 often shutdown automatica...”为内容创建页面

新页面

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

==== Environment ====
* May gpu760 of grid-14 be something wrong. To be exchanged.
* grid-11 often shutdown automatically
* grid-2/grid-10 have replaced the CPU fan.
* Add one hard disk to cuda.q machines.

==== Sparse DNN ====
* details at http://liuc.cslt.org/pages/sparse.html

==== RNN AM====
* Trying toolkit of Microsoft.(+)
* details at http://liuc.cslt.org/pages/rnnam.html

====Dropout & Maxout & retifier ====
* Drop out

* MaxOut && P-norm(+)
:* Need to solve the too small learning-rate problem
:** Add one normalization layer after the pnorm-layer
:** Add L2-norm upper bound
:* hold

====Convolutive network====
* Convolutive network(DAE)
:* http://cslt.riit.tsinghua.edu.cn/cgi-bin/cvss/cvss_request.pl?account=zhangzy&step=view_request&cvssid=311
:* To test real environment echo.(+)

:* Feature extractor
:** Technical report to draft, Yiye Lin, Shi Yin, Menyuan Zhao and Mian Wang

====DNN-DAE(Deep Atuo-Encode-DNN)====
:* Technical report to draft, Mengyuan Zhao and Zhiyong Zhang.
:* http://cslt.riit.tsinghua.edu.cn/cgi-bin/cvss/cvss_request.pl?account=zhangzy&step=view_request&cvssid=318
:* XueWei will reproduce the experiments.

====RNN-DAE(Deep based Atuo-Encode-RNN)====
:* http://cslt.riit.tsinghua.edu.cn/cgi-bin/cvss/cvss_request.pl?account=zhangzy&step=view_request&cvssid=261
:* HOLD

====VAD====
* Harmonics and Teager energy features.
* MPE training
* Test only Harmonic feature

====Speech rate training====
:* http://cslt.riit.tsinghua.edu.cn/cgi-bin/cvss/cvss_request.pl?account=zhangzy&step=view_request&cvssid=268
:* Technical report to draft. Shi Yin
:* Prepare for ChinaSIP

====Confidence====
* Reproduce the experiments on fisher dataset.
* Use the fisher DNN model to decode all-wsj dataset
* preparing scoring for puqiang data
* HOLD

====Neural network visulization====
:* http://cslt.riit.tsinghua.edu.cn/cgi-bin/cvss/cvss_request.pl?account=zhangzy&step=view_request&cvssid=324

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

===Language ID===
* GMM-based language is ready.
* Delivered to Jietong
* Prepare the test-case
* http://cslt.riit.tsinghua.edu.cn/cgi-bin/cvss/cvss_request.pl?account=zhangzy&step=view_request&cvssid=328

===Voice Conversion===
* Yiye is reading materials
* HOLD

==Text Processing==
===LM development===

====Domain specific LM====
* LM2.1
:* mix the sougou2T-lm,kn-discount continue
:* train a large lm using 25w-dict.(hanzhenglong/wxx)
::* find the problem in asr result
::* the model will finish (Tuesday)

====tag LM====
* Tag Lm
:* tag Probability should test add the weight(hanzhenglong) and handover to hanzhenglong ("this month")
:* run a tag demo('''this week''')
*paper
:* paper submit this week.
* similar word extension in FST
:* find similarity word using word2vec,word vector is training.
:* set the weight for word
:* set a proper test set
:* write a draft of a paper

====RNN LM====
*rnn
:* test wer RNNLM on Chinese data from jietong-data
:* generate the ngram model from rnnlm and test the ppl with different size txt.
*lstm+rnn
:* check the lstm-rnnlm code about how to Initialize and update learning rate.(hold)

===Word2Vector===

====W2V based doc classification====
* data prepare.
====Knowledge vector====
* Knowledge vector
:* Make a proper test set.
:* use text information and train word vector together.
:* Modify the object function and training process.
:* try to train on the whole data set
* result
:* 0.745->0.79, using yago for training.
====Character to word====
* Character to word conversion(hold)
===Translation===

* v5.0 demo released
:* cut the dict and use new segment-tool

===Sparse NN in NLP===
* review related paper

===QA===
====improve fuzzy match====
* add Synonyms similarity using MERT-4 method(hold)
====improve lucene search====
:* add more feature to improve search.
::* POS, NER ,tf ,idf ..
:* extract more features about lexical, syntactic and semantic to improve re-ranking performance.

====context framework====
* code for organization
:* change to knowledge graph

====query normalization====
* using NER to normalize the word

* new inter will install SEMPRE

@@ 第3行： / 第3行： @@
 ==== Environment ====
-* May gpu760 of grid-14 be something wrong. To be exchanged.
+* May gpu760 of grid-14 has been repairing.
-* grid-11 often shutdown automatically
+* grid-11 often shutdown automatically, too slow computation speed.
-* grid-2/grid-10 have replaced the CPU fan.
-* Add one hard disk to cuda.q machines.
-−
-==== Sparse DNN ====
-* details at http://liuc.cslt.org/pages/sparse.html
 ==== RNN AM====
 * details at http://liuc.cslt.org/pages/rnnam.html
-====Dropout & Maxout & retifier ====
+====Dropout & Maxout & rectifier ====
-* Drop out
+* Need to solve the too small learning-rate problem
+* 20h small scale sparse dnn with rectifier. --Chao liu
-* MaxOut && P-norm(+)
+* 20h small scale sparse dnn with Maxout/rectifier based on weight-magnitude-pruning. --Mengyuan Zhao
-:* Need to solve the too small learning-rate problem
-:** Add one normalization layer after the pnorm-layer
-:** Add L2-norm upper bound
-:* hold
 ====Convolutive network====
 * Convolutive network(DAE)
 :* http://cslt.riit.tsinghua.edu.cn/cgi-bin/cvss/cvss_request.pl?account=zhangzy&step=view_request&cvssid=311
-:* To test real environment echo.(+)
+:* Technical report to draft, Mian Wang, Yiye Lin, Shi Yin, Mengyuan Zhao
-−
-:* Feature extractor
-:** Technical report to draft, Yiye Lin, Shi Yin, Menyuan Zhao and Mian Wang
-====DNN-DAE(Deep Atuo-Encode-DNN)====
+====DNN-DAE(Deep Auto-Encode-DNN)====
-:* Technical report to draft, Mengyuan Zhao and Zhiyong Zhang.
+* Technical report to draft, Xiangyu Zeng, Shi Yin, Mengyuan Zhao and Zhiyong Zhang,
-:* http://cslt.riit.tsinghua.edu.cn/cgi-bin/cvss/cvss_request.pl?account=zhangzy&step=view_request&cvssid=318
+* http://cslt.riit.tsinghua.edu.cn/cgi-bin/cvss/cvss_request.pl?account=zhangzy&step=view_request&cvssid=318
-:* XueWei will reproduce the experiments.
-====RNN-DAE(Deep based Atuo-Encode-RNN)====
+====RNN-DAE(Deep based Auto-Encode-RNN)====
-:* 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
-:* HOLD
+* HOLD
 ====VAD====
-* Harmonics and Teager energy features.
+* DAE
-* MPE training
+* Technical report --Shi Yin
-* Test only Harmonic feature
 ====Speech rate training====

@@ 第82行： / 第82行： @@
 :* mix the sougou2T-lm,kn-discount continue
 :* train a large lm using 25w-dict.(hanzhenglong/wxx)
-::* find the problem in asr result
+::* add more data including poi, document information.
-::* the model will finish (Tuesday)
+::* add v1.0 vocab and filter the useless word
 ====tag LM====
 * Tag Lm
 :* tag Probability should test add the weight(hanzhenglong) and handover to hanzhenglong ("this month")
 * similar word extension in FST
 :* write a draft of a paper
+:* result :16.32->10.23
 ====RNN LM====
 *rnn
@@ 第110行： / 第105行： @@
 ====Knowledge vector====
 * Knowledge vector
-:* Make a proper test set.
+:* run the big data
-:* use text information and train word vector together.
+:* prepare the paper.
-:* Modify the object function and training process.
-:* try to train on the whole data set
 * result
 ====Character to word====
 * Character to word conversion(hold)
@@ 第124行： / 第116行： @@
 ===Sparse NN in NLP===
-* review related paper
+* write a technical report
 ===QA===
@@ 第133行： / 第125行： @@
 ::* POS, NER ,tf ,idf ..
 :* extract more features about lexical, syntactic and semantic to improve re-ranking performance.
+:* using sentence vector
 ====context framework====
 * code for organization