“ASR Status Report 2017-7-31”版本间的差异

2017年7月31日 (一) 04:40的最后版本

Date	People	Last Week	This Week
2017.7.31	Xiaofei Kang	Finish the Speaker Recognition experiment：mouth with candy, normal chat	Understand all the scripts of the Speaker Recognition experiment, and then learn to modify it.
	Miao Zhang	finish the experiments on five kinds of speech	optimize the vad parameter to improve the performance finish the new human test website
	Yanqing Wang	retraining task: experiments are in progress, some time needed.	all experiments should be done. TRP of retraining task.
	Ying Shi	apply mongodb and ajax on the data checking website with mongodb we are not depend on file lock anymore there is no need to save web state(except some cookie) after employ ajax continue to learn crawler	setup server for m2asr (use sheep02) design crawler program
	Yixiang Chen	plot tsne picture for 863 & fisher-5000 data set find why performance of wisper better than performance of chat	check data and paper
	Lantian Li	T-sne plot for speaker segmentation preparation [1]. check TASLP and NIPS paper.	deep spk recipe.
	Zhiyuan Tang	Updated the auto-scoring system with the newest version of Kaldi. Several patches need to be repaired. Kaldi book writing.	Initial version of auto-scoring system. Kaldi book writing.

Date	People	Last Week	This Week
2017.7.24	Xiaofei Kang	Prepare the data set of Speaker Recognition : pick out whisper Learn the the nnet3 model, run the nnet3 experiment	Learn the Speaker Recognition model, run the Speaker Recognition experiment
	Miao Zhang	joined a meeting in Chinese Academy of Social Sciences worked out a recording plan learnt kaldi and did experiments	test performances on 12 kinds of voices we have
	Hui Tang	help jiayin to configure dnn and lstm in kaldi	left for postgraduate life
	Yanqing Wang	change the source code of Kaldi to implement retraining ( with zero value fixed ) start to write a technical report of pruning the neural network ( not finished )	finish the retraining task finish the technical report
	Ying Shi	data checking website learn how to write a crawler program	write a more general crawler realign kazak train and test data with transfer learning model
	Yixiang Chen	use wisper audio for speaker recognition joined a meeting in Chinese Academy of Social Sciences	test performances on 12 kinds of voices
	Lantian Li	deepspk on TASLP. speaker segmentation.	recipe of deepspk.
	Zhiyuan Tang	Replaced ATLAS lib with MKL lib for compiling auto-scoring system. Kaldi book writing.	A basic demo for auto-scoring system. Kaldi book writing.

@@ 第6行： / 第6行： @@
 |Xiaofei Kang
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-* Finish the Speaker Recognition experiment：monuth with candy, normal chat
+* Finish the Speaker Recognition experiment：mouth with candy, normal chat
 ||
 * Understand all the scripts of the Speaker Recognition experiment, and then learn to modify it.
@@ 第48行： / 第48行： @@
 |Yixiang Chen
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-* check paper
 * plot tsne picture for 863 & fisher-5000 data set
 * find why performance of wisper better than performance of chat
@@ 第58行： / 第57行： @@
 |Lantian Li
 ||
-*
+* T-sne plot for speaker segmentation preparation [http://cslt.riit.tsinghua.edu.cn/mediawiki/images/e/e2/Spk_seg.pdf].
+* check TASLP and NIPS paper.
 ||
-*
+* deep spk recipe.
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