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| （某位用户的一个中间修订版本未显示） |
| 第89行： |
第89行： |
| | |Xueyi Wang | | |Xueyi Wang |
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| − | * | + | * carry out 1-d data experiment, and get the conclusion that feature we are using is not suitable for bayesian method |
| − | * | + | * make a summary of segmentation task I have done until now |
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| − | * | + | *modify the speech book |
| | + | *read papers and go through experiments of v-vector |
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| | * | | * |
| 第130行： |
第131行： |
| | |Haolin Chen | | |Haolin Chen |
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| − | * | + | * Continue learning statistics |
| − | * | + | * Read tutorials on ML |
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| − | * | + | * Continue learning ML，probability and statistics |
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| | * | | * |
| People |
This Week |
Next Week |
Task Tracking (DeadLine)
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| Yibo Liu
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| Xiuqi Jiang
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- Merge code with Yibo and clean up current Vivi
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- Polish up baselines and add extra regularizations to seq2seq loss
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| Jiayao Wu
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- made a summary of formal experiment
- prepare for the weekly report
- make a further try of Adaboost on ASR on chain model(to get rid of the influence of priors,no priors in chain model)
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- try more experiments on Adaboost ASR
- modify the speech book
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| Zhaodi Qi
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- Summarized the previous experiments and explored new methods.
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- Complete the experiment of Mult-scale information and Modify the speech book
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| Jiawei Yu
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- Continue phonetic attention experiment and write the experiment report.
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| Wenwei Dong
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- use frame fbank feature to train infogan, draw t-sne
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- use gmm to learn the distribution of different dataset
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| Xueyi Wang
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- carry out 1-d data experiment, and get the conclusion that feature we are using is not suitable for bayesian method
- make a summary of segmentation task I have done until now
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- modify the speech book
- read papers and go through experiments of v-vector
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| Ziya Zhou
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- Revise the speech book
- Get familiar with a simple ASR task
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| kaicheng li
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- Read SpecAugment, and acquired a sample demo form github
- Read tutorials. Revised a part of the speech book
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- Revise the speech book
- Verify the correctness of the SpecAugment demo
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| Haolin Chen
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- Continue learning statistics
- Read tutorials on ML
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- Continue learning ML，probability and statistics
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