“ASR:2015-01-12”版本间的差异

2015年1月12日 (一) 04:15的版本 （查看源代码） Lr（讨论 | 贡献） （以“==Speech Processing == === AM development === ==== Environment ==== * May gpu760 of grid-14 be something wrong. To be exchanged. ==== Sparse DNN ==== * details at...”为内容创建页面） 下一编辑→

（没有差异）

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2015年1月12日 (一) 04:15的版本

Speech Processing

AM development

Environment

• May gpu760 of grid-14 be something wrong. To be exchanged.

Sparse DNN

• details at http://liuc.cslt.org/pages/sparse.html
• need to test clean data
• MPE training to be continue

RNN AM

• Trying toolkit of Microsoft.(+)
• details at http://liuc.cslt.org/pages/rnnam.html

Dropout & Maxout & retifier

• Drop out

• Change the test data to more noisy data, to verify the effectiveness of dropout.

• 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
• Feature extractor
  • Combined with raw features, better performance obsearved.
  • Technical report to draft, Yiye Lin, Shi Yin, Menyuan Zhao and Mian Wang
• To test real enviroment echo.

DNN-DAE(Deep Atuo-Encode-DNN)

• test on XinWenLianBo music. results on
  • http://cslt.riit.tsinghua.edu.cn/cgi-bin/cvss/cvss_request.pl?account=zhaomy&step=view_request&cvssid=318
  • Technical report to draft, Mengyuan Zhao and Zhiyong Zhang.
• To test real enviroment echo.

VAD

• Harmonics and Teager energy features done.
• Model to be trained.

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

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(+)

Text Processing

LM development

Domain specific LM

• LM2.0

• mix the sougou2T-lm,kn-discount continue
• train a large lm using 25w-dict.(hanzhenglong/wxx)
• prun history lm(wxx)

• new dict.

• dongxu help zhenglong with large dictionary.

tag LM

• need to do

• tag Probability should test add the weight(hanzhenglong) and handover to hanzhenglong (hold)

paper

• paper submit this week.

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

• Initial results variable Bayesian GMM obtained. Performance is not as good as the conventional GMM.(hold)
• Non-linear inter-language transform: English-Spanish-Czch: wv model training done, transform model on investigation

Knowledge vector

• Knowledge vector

• Make a proper test set.
• Modify the object function and training process.

relation

Character to word

• Character to word conversion(hold)

Translation

• v5.0 demo released

• cut the dict and use new segment-tool

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 ..

XiaoI framework

• context in xiaoI
• make a report

query normalization

• using NER to normalize the word

• new inter will install SEMPRE