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| （4位用户的8个中间修订版本未显示） |
| 第10行： |
第10行： |
| | |Jingyi Lin | | |Jingyi Lin |
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| − | * | + | * -- |
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| − | * | + | * Concentrate on checking the cslt.book. |
| | + | * Prepare for the annual convention. |
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| 第19行： |
第20行： |
| | |Yanqing Wang | | |Yanqing Wang |
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| − | * | + | * 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: |
| | + | **[[媒体文件:GUI_distracted.png|distraction]] |
| | + | **[[媒体文件:GUI_focus.png|focus]] |
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| − | * | + | * (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 |
| | |- | | |- |
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| 第30行： |
第38行： |
| | |Hang Luo | | |Hang Luo |
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| − | * Continue joint training analysis work, but I'm very confused about how to improve
| + | * Compare decode result between mono and bi LM, and the decode result ues bi LM before and after joint |
| − | ||
| + | |
| − | * Compare decode result between mono and bi LM | + | |
| | * Choose wrong decode sentence and find its difference between baseline and shareGMM baseline | | * Choose wrong decode sentence and find its difference between baseline and shareGMM baseline |
| | * Finished ML book | | * Finished ML book |
| | + | || |
| | + | * Continue joint training analysis work, but I'm very confused about how to improve |
| | |- | | |- |
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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
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- run new AM by current speech data
- get more corpus from internet
- use current corpus make LM and decode
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| Yixiang Chen
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- 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
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| Lantian Li
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- LRE challenge on AP16-OL7.
- Jeju for APSIPA16.
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- LRE on AP16-OL7.
- Deep speaker embedding.
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| Zhiyuan Tang
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- A speech about recent ASR improvements.
- A supplementary TRP for "Multi-task Recurrent Model for True Multilingual Speech Recognition".
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| Date |
People |
Last Week |
This Week
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| 2016.12.12
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Yanqing Wang
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- read a paper about driving distraction detection task
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- show normal/distraction patterns of a driver with one class and two class SVM
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| Hang Luo
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- Compared mono-language model and bi-language model decode result.
- Read paper of WFST.
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- Use different corpus or generate mix-lingual corpus to run experiments
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| Ying Shi
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- work from Chao Xing down
- kazak lm
- got some corpus from a student who study in Minzu University of China.But the corpus is short (about 10000) so the ppl is also poor.
- spider
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| Yixiang Chen
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- Complete the replay task experiment and report
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- learning tensorflow coding DNN and CNN net
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| Lantian Li
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- interim report done;
- PPT for APSIPA16;
- LRE challenge on AP16-OL7.
- Deep speaker embedding restart!
- Submit TRP-20160011 on Replay detection.
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| Zhiyuan Tang
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- interim report done;
- PPT for APSIPA16;
- language mask[1]
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