“2019-05-10”版本间的差异

2019年5月11日 (六) 11:02的最后版本

People	This Week	Next Week
Yibo Liu
Xiuqi Jiang	Merge code with Yibo and clean up current Vivi	Polish up baselines and add extra regularizations to seq2seq loss
Jiayao Wu	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)	try more experiments on Adaboost ASR modify the speech book
Zhaodi Qi	Summarized the previous experiments and explored new methods.	Complete the experiment of Mult-scale information and Modify the speech book
Jiawei Yu	Continue phonetic attention experiment and write the experiment report.	...
Wenwei Dong	use frame fbank feature to train infogan, draw t-sne	use gmm to learn the distribution of different dataset
Xueyi Wang	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	modify the speech book read papers and go through experiments of v-vector
Ziya Zhou	Read a tutorial on ASR	Revise the speech book Get familiar with a simple ASR task
kaicheng li	Read SpecAugment, and acquired a sample demo form github Read tutorials. Revised a part of the speech book	Revise the speech book Verify the correctness of the SpecAugment demo
Haolin Chen	Continue learning statistics Read tutorials on ML	Continue learning ML，probability and statistics

@@ 第89行： / 第89行： @@
 |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
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+* 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116行： / 第117行： @@
 |kaicheng li
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+* Read SpecAugment, and acquired a sample demo form github
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+* 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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@@ 第129行： / 第131行： @@
 |Haolin Chen
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+* Continue learning statistics
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+* Read tutorials on ML
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+* Continue learning ML，probability and statistics
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