“ASR:2014-12-29”版本间的差异
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(以“==Text Processing== ===LM development=== ====Domain specific LM==== * LM2.0 :* data check for lexicon(jietong) :* merge lm with NAME POI etc.(hanzhenglong) :* mix...”为内容创建页面) |
(→Domain specific LM) |
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第5行: | 第5行: | ||
* LM2.0 | * LM2.0 | ||
:* data check for lexicon(jietong) | :* data check for lexicon(jietong) | ||
− | :* merge lm with NAME POI etc.(hanzhenglong) | + | :* merge lm with NAME POI etc.(hanzhenglong/wxx) |
:* mix the sougou2T-lm,kn-discount continue | :* mix the sougou2T-lm,kn-discount continue | ||
− | :* train a large lm using 25w-dict. | + | :* train a large lm using 25w-dict.(hanzhenglong/wxx) |
− | :* | + | :* prun history lm(wxx) |
* new dict. | * new dict. | ||
:* dongxu help zhenglong with large dictionary. | :* dongxu help zhenglong with large dictionary. | ||
+ | |||
====tag LM==== | ====tag LM==== | ||
* need to do | * need to do |
2014年12月29日 (一) 06:23的版本
Text Processing
LM development
Domain specific LM
- LM2.0
- data check for lexicon(jietong)
- merge lm with NAME POI etc.(hanzhenglong/wxx)
- mix the sougou2T-lm,kn-discount continue
- train a large lm using 25w-dict.(hanzhenglong/wxx)
- prun history lm(wxx)
- new dict.
- dongxu help zhenglong with large dictionary.
tag LM
- need to do
- tag Probability should test add the weight(hanzhenglong) and handover to hanzhenglong (hold)
- paper
- modify the paper(yuanb two days),paper submit 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
- Make a proper test set.
- Modify the object function and training process.
- Read Liu's paper.
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
improve fuzzy match
- add Synonyms similarity using MERT-4 method(hold)
improve lucene search
- add more feature to improve search.
XiaoI framework
- context in xiaoI
query normalization
- using NER to normalize the word
- new inter will install SEMPRE