ASR:2015-03-16

Text Processing

LM development

Domain specific LM

• LM2.X

• train a large lm using 25w-dict.(hanzhenglong/wxx)

• v2.0c filter the useless word.(next week)
• set the test set for new word (hold)

• prepare the wiki data: entity list.

tag LM

• Tag Lm(JT)

• error check

• similar word extension in FST

• repeat the experiment using same data

RNN LM

• rnn

• the input and output is word embedding and add some token information like NER..
• map the word to character and train the lm.

• lstm+rnn

• check the lstm-rnnlm code about how to Initialize and update learning rate.(hold)

Word2Vector

W2V based doc classification

• data prepare.(hold)

Knowledge vector

• make a report on Monday

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.

QA

improve fuzzy match

• add Synonyms similarity using MERT-4 method(hold)

online learning

• data is ready.prepare the ACL paper

• prepare sougouQ data and test it using current online learning method

framework

• extract the module

• extract the context module ,search module,entity recognize module and common module.
• define the inference in different modules

• composite module

leftover problem

• new inter will install SEMPRE