2015年8月24日 (一) 01:18的版本 （查看源代码） Xingchao（讨论 | 贡献） （以“==Speech Processing == === AM development === ==== Environment ==== * grid-14 is on repairation * prepare to buy a server ==== RNN AM==== *train monophone RNN --zh...”为内容创建页面）		2015年8月24日 (一) 01:33的版本 （查看源代码） Xingchao（讨论 | 贡献） （→‎RNN Rank Task） 下一编辑→
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	====RNN Rank Task====		====RNN Rank Task====
		+	:* Test.
	:*Paper: RNN Rank Net.		:*Paper: RNN Rank Net.
	* (hold)		* (hold)
		+	* Output rank information.
	====Graph RNN====		====Graph RNN====

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2015年8月24日 (一) 01:33的版本

Speech Processing

AM development

Environment

• grid-14 is on repairation
• prepare to buy a server

RNN AM

• train monophone RNN --zhiyuan
• train using 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

• hold

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

• Test.
• Paper: RNN Rank Net.

• (hold)
• Output rank information.

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 <--> 08-17)

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.

• (hold)

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 (hold)

• Adaboost method

• 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