“ASR:2015-02-09”版本间的差异

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第62行： 第62行：
 
====Domain specific LM====
 
====Domain specific LM====
 
* LM2.X
 
* LM2.X
−
:* mix the sougou2T-lm,kn-discount continue
+
:* mix the sougou2T-lm,kn-discount(done)
 
:* train a large lm using 25w-dict.(hanzhenglong/wxx)
 
:* train a large lm using 25w-dict.(hanzhenglong/wxx)
 
::* v2.0a adjust the weight and smaller weight of transcription is better.(done)
 
::* v2.0a adjust the weight and smaller weight of transcription is better.(done)
第71行： 第71行：
 
====tag LM====
 
====tag LM====
 
* Tag Lm
 
* Tag Lm
−
:* code is given to jietong .
+
:* add 3-class tag and test
 
* similar word extension in FST
 
* similar word extension in FST
−
:* write a draft of a paper
+
:* improve the key-word weight in G , and result is good in keyword recognization
−
:* result [http://cslt.riit.tsinghua.edu.cn/cgi-bin/cvss/cvss_request.pl?account=mx&step=view_request&cvssid=332]
+
:* read to deal with the English-Chinese
  
 
====RNN LM====
 
====RNN LM====

2015年2月9日 (一) 02:39的版本

Speech Processing

AM development

Environment

  • May gpu760 of grid-14 has been repairing.
  • grid-11 often shutdown automatically, too slow computation speed.

RNN AM

Mic-Array

  • XueWei is reading papers and preparing the technical report

Dropout & Maxout & rectifier

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

Convolutive network

  • Convolutive network(DAE)

DNN-DAE(Deep Auto-Encode-DNN)

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

VAD

  • DAE
  • HOLD
  • Technical report -- Shi Yin

Speech rate training

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

Speaker ID


Text Processing

LM development

Domain specific LM

  • LM2.X
  • mix the sougou2T-lm,kn-discount(done)
  • train a large lm using 25w-dict.(hanzhenglong/wxx)
  • v2.0a adjust the weight and smaller weight of transcription is better.(done)
  • v2.0b add the v1.0 vocab(this week)
  • v2.0c filter the useless word.(next week)
  • set the test set for new word (hold)

tag LM

  • Tag Lm
  • add 3-class tag and test
  • similar word extension in FST
  • improve the key-word weight in G , and result is good in keyword recognization
  • read to deal with the English-Chinese

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

  • run the big data
  • prepare the paper.

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

  • write a technical report(Wednesday) and make a report.

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
  • result:P@1: 0.68734335-->0.7763158P@5: 0.80325814-->0.8383459 [1]
  • Optimize the code about extracting features and reranking and commit to Rong Liu to check in.
  • using sentence vector, it doesn't work.

online learning

  • a simple edition about online learning part about QA.

context framework

  • code for organization

query normalization

  • using NER to normalize the word
  • new inter will install SEMPRE
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