“2024-05-06”版本间的差异

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（10位用户的15个中间修订版本未显示）
第6行： 第6行：
 
|Dong Wang
 
|Dong Wang
 
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* AIGraph Slides Done
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* Slides for several presentations
 
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第17行： 第18行：
 
|Lantian Li
 
|Lantian Li
 
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* GPU status [https://z1et6d3xtb.feishu.cn/wiki/XGcGwRK5viJmpRkjH9AczIhynCh]
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* Projects (AED -> MobileNet, TSE -> Data/Exp)
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* ASIP-BUPT (NeuralScoring, CohortSS)
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* IS rebuttal
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* Rabbit05
 
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第62行： 第67行：
 
|Chen Chen
 
|Chen Chen
 
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* Prepare for CNVSRC2024
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* About 50 hours new data
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* Paper reading
 
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第86行： 第93行：
 
|Zehua Liu
 
|Zehua Liu
 
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* Crop size Exp
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* AKVSR training
 
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第111行： 第119行：
 
|Wan Lin
 
|Wan Lin
 
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* Neural Scoring
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** EAASP in Sunine (training)
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** Adjust BCE loss
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* Revise graduation paper
 
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第122行： 第133行：
 
|Tianhao Wang
 
|Tianhao Wang
 
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* Neural Scoring: use wespeaker, can't reach the performance of sunine [https://z1et6d3xtb.feishu.cn/docx/BywjdkGvNou12sxQ4dAcxYa9noh]
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* SpEx+ training ...
 
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第133行： 第145行：
 
|Zhenyu Zhou
 
|Zhenyu Zhou
 
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*data collection[https://z1et6d3xtb.feishu.cn/docx/ZgkUdxHbOo7MWoxjDw2c7RIHnYc]
 
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第145行： 第157行：
 
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* Graduation paper
 
* Graduation paper
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* Neural Scoring: use large pretrain model(wav2vec2.0) as test encoder, seems useless.(Mix trial EER: 9%)
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* Neural Scoring: use large pretrain model(wav2vec2.0) as test encoder.
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** seems useless.(Mix trial EER: 9%)
 
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第169行： 第182行：
 
|Yu Zhang
 
|Yu Zhang
 
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* Debugging for evalml (some mismatch in training and testing)
 
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第192行： 第205行：
 
|Yang Wei
 
|Yang Wei
 
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* Double check reliability of the baseline model for children MDD challenge
 
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第202行： 第215行：
 
|Lily
 
|Lily
 
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* Prepare for AI Radiance ceremony
 
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2024年5月6日 (一) 11:01的最后版本

People This Week Next Week Task Tracking (DeadLine)
Dong Wang
  • AIGraph Slides Done
  • Slides for several presentations
Lantian Li
  • GPU status [1]
  • Projects (AED -> MobileNet, TSE -> Data/Exp)
  • ASIP-BUPT (NeuralScoring, CohortSS)
  • IS rebuttal
  • Rabbit05
Ying Shi
Zhenghai You
  • Model adjustment for Huawei project[2][3]
  • Data collection for Huawei projects
Junming Yuan
  • KWS project code refactoring
  • Control FA experiment baseline result[4]
Chen Chen
  • Prepare for CNVSRC2024
  • About 50 hours new data
  • Paper reading
Xiaolou Li
  • CNVSRC2024 E-Branchformer test
    • better on multi but worse on single
  • Paper reading
Zehua Liu
  • Crop size Exp
  • AKVSR training
Pengqi Li
  • Extend Experiment on Timit[5]
    • Training and analysis: Assume the models has content bias(Unreliable)
    • Try to use larger data training to resist this bias.
    • Statistics di-phone On Audio-Mnist
Wan Lin
  • Neural Scoring
    • EAASP in Sunine (training)
    • Adjust BCE loss
  • Revise graduation paper
Tianhao Wang
  • Neural Scoring: use wespeaker, can't reach the performance of sunine [6]
  • SpEx+ training ...
Zhenyu Zhou
  • data collection[7]
Junhui Chen
  • Graduation paper
  • Neural Scoring: use large pretrain model(wav2vec2.0) as test encoder.
    • seems useless.(Mix trial EER: 9%)
Jiaying Wang
  • data collection for huawei project
  • continue cohort experiment [8]
  • reproduced another baseline DPTNet(waiting for test)
Yu Zhang
  • Debugging for evalml (some mismatch in training and testing)
Wenqiang Du
  • add apeed perturb、larg negative data、human voice interference to update kws model(completed)
  • Some tests have not completed
Yang Wei
  • Double check reliability of the baseline model for children MDD challenge
Lily
  • Prepare for AI Radiance ceremony
Turi
  • Data collection
    • 23K so far
    • Downloaded the data and randomly checking some audios for each users
Yue Gu
Qi Qu
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