“ASR Status Report 2017-6-5”版本间的差异

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|Yanqing Wang
 
|Yanqing Wang
 
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* [http://192.168.0.51:5555/cgi-bin/cvss/cvss_request.pl?account=wangyanqing&step=view_request&cvssid=609 sparse dnn with different threshold]
 
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* continue the experiment
 
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* OLR17(Ten lans) i-vector / L-vector + svm baseline
 
* OLR17(Ten lans) i-vector / L-vector + svm baseline
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* "cough, laugh, hello" data for speaker identification
 
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* (cough, laugh, hello) data for speaker identification
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* go on the two tasks.
 
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|Lantian Li   
 
|Lantian Li   
 
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* End-to-end ASV [http://192.168.0.51:5555/cgi-bin/cvss/cvss_request.pl?account=lilt&step=view_request&cvssid=611]
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* Deep speaker feature learning.
 
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* Speaker diarization.
 
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2017年6月5日 (一) 04:25的最后版本

Date People Last Week This Week
2017.6.5


Hui Tang
  • created a database for speech overlap
  • experiments with speech overlap

here

  • align data before overlap
  • test in lstm,tdnn
Yanqing Wang
  • continue the experiment
Ying Shi
  • mix-lingual structure (without LID)
    • the performance of thch30 is bad than baseline 24.84
    • the performance of kazak is better than baseline 24.37
    • the performance of uyghur is very bad 109.01
  • result analysis
    • pdf mix
    • the language model of uyghur is too weak
  • work for APSIPA2017
Yixiang Chen
  • OLR17(Ten lans) i-vector / L-vector + svm baseline
  • "cough, laugh, hello" data for speaker identification
  • go on the two tasks.
Lantian Li
  • End-to-end ASV [1]
  • Deep speaker feature learning.
  • Speaker diarization.
Zhiyuan Tang
  • basic recipes for OLR17 and MixASR17
  • improve the recipes and publish


Date People Last Week This Week
2017.5.31


Hui Tang
  • after introducing beamforming, zhiyong lets me learn something about how to sound localization
  • Create a database for overlapping speech
Yanqing Wang
Ying Shi
  • work for Apsipa17
    • thchs baseline
    • kazakh baseline
    • uyghur baseline
    • 3 language merge GMM baseline
  • work for Apsipa17
  • graduation thesis
Yixiang Chen
Lantian Li
  • Submit the Interspeech paper.
  • Deep speaker feature learning with a larger ASR model.
  • Prepare the end-to-end ASV.
  • End-to-end ASV.
Zhiyuan Tang
  • Experiments for OC17 mix-asr challenge,baseline done.
  • Spk feature as LID input.
  • Data preparation for AP17 orl challenge.
  • Two challenges done.
取自“http://index.cslt.org/mediawiki/index.php?title=ASR_Status_Report_2017-6-5&oldid=27352”