ASR Status Report 2017-7-17

Date	People	Last Week	This Week
2017.7.17	Miao Zhang	Read the paralinguistic paper and material from Teacher Li work out the recording plan (delayed)	work out the recording plan with instruction from Teacher Li check the book of deep learning
	Hui Tang	finish checking the speech database help jiayin learn kaldi by training a language identification model	make sure which type of voice is what we need help jiayin to configure dnn and lstm in kaldi
	Yanqing Wang	check the former conclusions in a narrow network ( not finished yet ) read the source code as a preparation for retrain task.	finish checking the former conclusions and try to find the applicable conditions. finish the retrain task.
	Ying Shi	kazak transfer learning (WER) dark:16.50 fix:18.33 org:23.69 data checking website major function has been down save state when refresh or close the page is in progress	finish the website(employ text database) design more powerfull crawler
	Yixiang Chen	Through voiceprint spectrum synthetic speech read paralinguistic and challenge of paralinguistic 2009-2017	share paralinguistic
	Lantian Li
	Zhiyuan Tang	Replace the old version kaldi with new ones. (delayed) Gather Part 1: 'Speech, Speech Processing and Tools' of Kaldi book for further release. (delayed)	Replace the old version kaldi with new ones. Gather Part 1: 'Speech, Speech Processing and Tools' of Kaldi book for further release.

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Date	People	Last Week	This Week
2017.7.10	Miao Zhang	A report about trivial events Finish the test website with Tanghui	Read the paper of Paralinguistics Make a plan for recording and start to record hopefully.
	Hui Tang	completed the test web site web finished checking the subset of our speech databases (nearly 800 sentences)	finish checking the reminder of the databases (nearly 2500 sentences)
	Yanqing Wang	use different activation function to prune result	make the network narrow and test the former conclusions. change source code to retrain the neural network.
	Ying Shi	help zheling to finish his first crawler program chech hazak speech data train: 1346 utterances' WER large than 20% (utterance level WER) test: 759 utterances' WER large than 20%(utterance level WER) transfer learning based on th30 and wsj (performance is poor)	tools for speech data checking transfer learning based on large Chinese ASR model
	Yixiang Chen	plot for “learning deep speaker features”	comprehend Paralinguistics record voice
	Lantian Li	deep speaker feature segmentation is still not suitable. visualization with the t-sne seems cool. help Zhangzy decode d-vector and re-train a new deep speaker model.	more details of segmentation experiments. prepare the weekly meeting.
	Zhiyuan Tang	Scanned the source code of auto-scoring system; A report about the research of the speech group (Thursday).	Replace the old version kaldi with new ones. Gather Part 1: 'Speech, Speech Processing and Tools' of Kaldi book for further release.