“2024-04-08”版本间的差异

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（13位用户的26个中间修订版本未显示）
第34行： 第34行：
 
|Ying Shi
 
|Ying Shi
 
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* Detect wake-up words from Continuous speech Down
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* SPL Paper, almost down
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* [https://z1et6d3xtb.feishu.cn/wiki/DYSjw7LfviU7u1kWbhEcFjE1nld?from=from_copylink Group Work]
 
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第45行： 第47行：
 
|Zhenghai You
 
|Zhenghai You
 
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* Checked the code of mini loss[https://z1et6d3xtb.feishu.cn/docx/AnDZd7ZeGovaPzxgqCncnSIJnvg]
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* Test onnx of Huawei project[https://z1et6d3xtb.feishu.cn/wiki/LTejwFN3KisChhkRngzcN5Kxn0c]
 
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第66行： 第69行：
 
|Chen Chen
 
|Chen Chen
 
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* Finished my thesis :)
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* Group work [https://z1et6d3xtb.feishu.cn/docx/FvXjdKWH1oejYgxnjFwcQKFan8g?from=from_copylink]
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** finish training for most of the structures, but all performs a little worse
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** no good news from KD
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** good primary experiment result from char as modeling unit, need to check after whole training
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** 58 hours for CN-CVS II (too slow)
 
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* Try some data aug methods for VSR (Crop size)
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* Help with entropy analyze of child data
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* START ICASSP2024 PAPER READING
 
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第77行： 第87行：
 
|Xiaolou Li
 
|Xiaolou Li
 
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* Reproduce different VSR structure [https://z1et6d3xtb.feishu.cn/docx/BgD4djeTioCgd6xjFXNcBXXLnKg?from=from_copylink]
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** interCTC, Resnet3D frontend, Branchformer, E-Branchformer
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* Paper reading
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** Mamba, icassp2024
 
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* modify E-Branchformer
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* Resnet3D frontend + Branchformer test
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* s4 decoder (maybe), mamba paper learning
 
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第88行： 第103行：
 
|Zehua Liu
 
|Zehua Liu
 
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* read papper
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* auxiliary loss code[https://z1et6d3xtb.feishu.cn/docx/ZaTFd3A5EoK982xWBVschloanee?from=from_copylink]
 
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第99行： 第115行：
 
|Pengqi Li
 
|Pengqi Li
 
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* Summary[https://z1et6d3xtb.feishu.cn/docx/Mt46dqE8UoBnuBxu7q8cPletnzb] of speech processing XAI for NSFC
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** polish, reference, v1(90%)
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* Workshop report(video, slide, poster)
 
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第110行： 第128行：
 
|Wan Lin
 
|Wan Lin
 
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* Graduation paper
 
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第121行： 第139行：
 
|Tianhao Wang
 
|Tianhao Wang
 
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* EA-ASP (from SJTU) reproduced successfully [https://z1et6d3xtb.feishu.cn/docx/BywjdkGvNou12sxQ4dAcxYa9noh]
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** EA-ASP implement, wespeaker toolkit modification, training pairs construction totally according to the paper
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** get the better EER(4.021%) comparing to the paper (5.212%) on Vox1-O-Overlap
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** evaluation on our trials (concat and weak_overlap are better, overlap and mix are worse)
 
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第143行： 第164行：
 
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|Junhui Chen
 
|Junhui Chen
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* Neural scoring with Frequency-channel attention
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** Our overlap test trial: EER 7.382% -> 7.132%
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* Graduation paper
 
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第155行： 第178行：
 
|Jiaying Wang
 
|Jiaying Wang
 
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* HHuawei project:train speakerbeam on -4,4,converge,some bug in test
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* cohort mini loss: check code & test
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第166行： 第191行：
 
|Yu Zhang
 
|Yu Zhang
 
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* Financial Backtesting pipline
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** remake Stock and Industry return logic
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** debug Brinson Analysis result
 
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* Use SAC as a baseline to run through the entire process from training to policy generation to backtesting
 
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第189行： 第216行：
 
|Yang Wei
 
|Yang Wei
 
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* Fix problems about ASR model for mispronunciation detection task
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* Prepare the baseline system
 
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第199行： 第227行：
 
|Lily
 
|Lily
 
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* Data Analysis
 
* Paper Reading[https://z1et6d3xtb.feishu.cn/docx/L0jGdCqEXouL8hx8kelcrJzjn8d?from=from_copylink]
 
* Paper Reading[https://z1et6d3xtb.feishu.cn/docx/L0jGdCqEXouL8hx8kelcrJzjn8d?from=from_copylink]
 
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2024年4月8日 (一) 10:58的最后版本

People This Week Next Week Task Tracking (DeadLine)
Dong Wang
  • Primary AI design
  • NMI neuralmag paper submitted
Lantian Li
  • GPU status [1]
  • Projects (POC of Cough/Humming detection, TSE proposal)
  • ASIP-BUPT (NeuralScoring, CohortTSE)
  • AI Course Polish
  • Machine Moving
  • New machine (rabbit04)
Ying Shi
  • Detect wake-up words from Continuous speech Down
  • SPL Paper, almost down
  • Group Work
Zhenghai You
  • Checked the code of mini loss[2]
  • Test onnx of Huawei project[3]
Junming Yuan
  • Experimental report on "learn not to listen" v3 extend test[4]
Chen Chen
  • Finished my thesis :)
  • Group work [5]
    • finish training for most of the structures, but all performs a little worse
    • no good news from KD
    • good primary experiment result from char as modeling unit, need to check after whole training
    • 58 hours for CN-CVS II (too slow)
  • Try some data aug methods for VSR (Crop size)
  • Help with entropy analyze of child data
  • START ICASSP2024 PAPER READING
Xiaolou Li
  • Reproduce different VSR structure [6]
    • interCTC, Resnet3D frontend, Branchformer, E-Branchformer
  • Paper reading
    • Mamba, icassp2024
  • modify E-Branchformer
  • Resnet3D frontend + Branchformer test
  • s4 decoder (maybe), mamba paper learning
Zehua Liu
  • read papper
  • auxiliary loss code[7]
Pengqi Li
  • Summary[8] of speech processing XAI for NSFC
    • polish, reference, v1(90%)
  • Workshop report(video, slide, poster)
Wan Lin
  • Graduation paper
Tianhao Wang
  • EA-ASP (from SJTU) reproduced successfully [9]
    • EA-ASP implement, wespeaker toolkit modification, training pairs construction totally according to the paper
    • get the better EER(4.021%) comparing to the paper (5.212%) on Vox1-O-Overlap
    • evaluation on our trials (concat and weak_overlap are better, overlap and mix are worse)
Zhenyu Zhou
  • Finish NeuralScoring baseline[10]
  • ICASSP2024 report
Junhui Chen
  • Neural scoring with Frequency-channel attention
    • Our overlap test trial: EER 7.382% -> 7.132%
  • Graduation paper
Jiaying Wang
  • HHuawei project:train speakerbeam on -4,4,converge,some bug in test
  • cohort mini loss: check code & test
Yu Zhang
  • Financial Backtesting pipline
    • remake Stock and Industry return logic
    • debug Brinson Analysis result
  • Use SAC as a baseline to run through the entire process from training to policy generation to backtesting
Wenqiang Du
  • Some model update task
    • Chinese and Uyghur
Yang Wei
  • Fix problems about ASR model for mispronunciation detection task
  • Prepare the baseline system
Lily
  • Data Analysis
  • Paper Reading[11]
Qi Qu
  • First day
  • Dev environment setup
Turi
  • Prepared sentences
  • Prepared data collection app for release
取自“http://index.cslt.org/mediawiki/index.php?title=2024-04-08&oldid=41593”