ASR:2015-07-13

Speech Processing

AM development

==== Environment ====*

• the GPU of grid-14 does not work

RNN AM

• hold
• morpheme RNN --zhiyuan
• train using large dataset--mengyuan

Mic-Array

• hold
• compute EER with kaldi

====Data selection unsupervised learning

• acoustic feature based submodular using Pinan dataset --zhiyong

RNN-DAE(Deep based Auto-Encode-RNN)

• hold
• 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 --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

Dark knowledge

• test random last output layer when train MPE --zhiyuan

language vector

• train using language vector with the dataset of 1400h_CN + 100h_EN--mengyuan
• write a paper--zhiyuan

rectifier

• WER performs worse using auraro4 --zhiyuan
• train using other dataset
• rectifier RNN

audio embedding=

• audio ebedding --Wei Xu

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)

Order representation

• Nested Dropout
• modify the objective function(hold)

Balance Representation

• Find error signal

Recommendation

• Reproduce baseline.

DSSM based QA

• Pre-processing java class.

• Reproduce baseline.

Seq to Seq(09-15)

• Review papers

• Reproduce baseline.

Text Group Intern Project

• ====Buddhist Process====

(hold)

RNN Poem Process

(hold)

RNN Document Vector

(hold)

Image Baseline

(hold)