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| 第67行： |
第67行： |
| | |Zhiyuan Tang | | |Zhiyuan Tang |
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| − | * | + | * TRP of "How to Config Kaldi nnet3 (in Chinese)", not finished yet; |
| | + | * outline of TRP for "Multi-task Recurrent Model for True Multilingual Speech Recognition". |
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| − | * | + | * Finish the above 2 TRPs. |
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| Date |
People |
Last Week |
This Week
|
| 2016.12.19
|
Jingyi Lin
|
|
- Concentrate on checking the cslt.book.
- Prepare for the annual convention.
|
| Yanqing Wang
|
- build a data sender ( read & generate txt files of distracted feature )
- build a data analyzer ( detect the modification of files and make response ( show tokens ) )
- screenshot:
|
- (maybe) replace the detection mechanism by socket
- find best parameters to avoid over-fitting
- add two-class SVM to the program
- make GUI more pretty and easy to use
|
| Hang Luo
|
- Compare decode result between mono and bi LM, and the decode result ues bi LM before and after joint
- Choose wrong decode sentence and find its difference between baseline and shareGMM baseline
- Finished ML book
|
- Continue joint training analysis work, but I'm very confused about how to improve
|
| Ying Shi
|
- some work about kazak lm
- crawl data from kazak internet
|
- run new AM by current speech data
- get more corpus from internet
- use current corpus make LM and decode
|
| Yixiang Chen
|
- Leanring tensorflow
- coding pair wise net use tensorflow
- alter CNN
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- coding CNN connect pair wise
- Dealing with the issue of different lengths of voice
|
| Lantian Li
|
- LRE challenge on AP16-OL7.
- Jeju for APSIPA16.
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- LRE on AP16-OL7.
- Deep speaker embedding.
|
| Zhiyuan Tang
|
|
- A speech about recent ASR improvements.
- A supplementary TRP for "Multi-task Recurrent Model for True Multilingual Speech Recognition".
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