“ASR:2014-12-08”版本间的差异
来自cslt Wiki
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====Domain specific LM==== | ====Domain specific LM==== | ||
* domain lm | * domain lm | ||
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:* Sougou2T : kn-count. | :* Sougou2T : kn-count. | ||
:* lm v2.0 continue('''this week''') | :* lm v2.0 continue('''this week''') |
2014年12月8日 (一) 02:21的版本
Text Processing
LM development
Domain specific LM
- domain lm
- Sougou2T : kn-count.
- lm v2.0 continue(this week)
- new dict.
- Released vocab v2.0 (mainly done by Dongxu) to JieTong.
- some problem
- using minimum size segmentation and artificial add the long word(like 中华人民共和国)
- check the v2.0-dict with small data.
tag LM
- summary done
- need to do
- tag Probability should test add the weight(hanzhenglong) and handover to hanzhenglong (hold)
- make a summary about tag-lm and journal paper(wxx and yuanb)(this weeks).
- Reviewed papers and begin to write paper (this week)
RNN LM
- rnn
- test wer RNNLM on Chinese data from jietong-data(this week)
- generate the ngram model from rnnlm and test the ppl with different size txt.[1]
- 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 started
- Analysis the wiki infomation of category and link into jso done, knowledge vector build graph done.
- begin to code for train
relation
- Accomplish transE with almost the same performance as the paper did(even better)[2]
Character to word
- Character to word conversion(hold)
- prepare the task: word similarity
- prepare the dict.
Translation
- v5.0 demo released
- cut the dict and use new segment-tool
QA
deatil:
Spell mistake
- add the xiaoI pingyin correct to framework.
improve fuzzy match
- add Synonyms similarity using MERT-4 method(hold)
improve lucene search
- using MERT-4 method to get good value of multi-feature.like IDF,NER,baidu_weight,keyword etc.(liurong this month)
- now test the performance.
Multi-Scene Recognition
- done
XiaoI framework
- ner from xiaoI
- new inter will install SEMPRE
patent
- done