“ASR:2015-03-30”版本间的差异

来自cslt Wiki
跳转至: 导航搜索
Lr讨论 | 贡献
W2V based doc classification
第60行: 第60行:
  
 
====W2V based doc classification====
 
====W2V based doc classification====
* data prepare.
+
* corpus ready
*  
+
* learn some benchmark.
 +
 
 
===Translation===
 
===Translation===
 
* v5.0 demo released
 
* v5.0 demo released

2015年3月30日 (一) 08:35的版本

Speech Processing

AM development

Environment

  • grid-11 often shut down automatically, too slow computation speed.
  • GPU has being repired.--Xuewei

RNN AM


Mic-Array

  • investigate alpha parameter in time domian and frquency domain

Dropout & Maxout & rectifier

  • HOLD
  • Need to solve the too small learning-rate problem
  • 20h small scale sparse dnn with rectifier. --Mengyuan
  • 20h small scale sparse dnn with Maxout/rectifier based on weight-magnitude-pruning. --Mengyuan Zhao

Convolutive network

  • HOLD
  • CNN + DNN feature fusion
  • reproduce experiments -- Yiye

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

Speech rate training

Neural network visulization

Speaker ID

Ivector based ASR

Text Processing

tag LM

  • similar word extension in FST
  • check the formula using Bays and experiment

RNN LM

  • rnn
  • code the character-lm using Theano
  • lstm+rnn
  • check the lstm-rnnlm code about how to Initialize and update learning rate.(hold)

W2V based doc classification

  • corpus ready
  • learn some benchmark.

Translation

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

Sparse NN in NLP

  • prepare the ACL
  • check the code to find the problem .
  • increase the dimension
  • use different test set,but the result is not good.

online learning

  • data is ready.prepare the ACL paper
  • prepare sougouQ data and test it using current online learning method
  • baseline is not normal.