ASR Status Report 2016-12-19

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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
  • run new AM by current speech data
  • get more corpus from internet
  • use current corpus make LM and decode
Yixiang Chen
  • Leanring tensorflow
  • coding pair wise net use tensorflow
  • alter CNN
  • coding CNN connect pair wise
  • Dealing with the issue of different lengths of voice
Lantian Li
  • LRE challenge on AP16-OL7.
  • Jeju for APSIPA16.
  • LRE on AP16-OL7.
  • Deep speaker embedding.
Zhiyuan Tang
  • Jeju for APSIPA16.
  • A speech about recent ASR improvements.
  • A supplementary TRP for "Multi-task Recurrent Model for True Multilingual Speech Recognition".




Date People Last Week This Week
2016.12.12


Yanqing Wang
  • read a paper about driving distraction detection task
  • show normal/distraction patterns of a driver with one class and two class SVM
Hang Luo
  • Compared mono-language model and bi-language model decode result.
  • Read paper of WFST.
  • Use different corpus or generate mix-lingual corpus to run experiments
Ying Shi
  • 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
  • kazak lm
Yixiang Chen
  • Complete the replay task experiment and report
  • learning tensorflow coding DNN and CNN net
Lantian Li
  • interim report done;
  • PPT for APSIPA16;
  • LRE challenge on AP16-OL7.
  • Deep speaker embedding restart!
  • Submit TRP-20160011 on Replay detection.
  • Jeju for APSIPA16.
Zhiyuan Tang
  • interim report done;
  • PPT for APSIPA16;
  • language mask[1]
  • Jeju for APSIPA16.