“2024-12-02”版本间的差异

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（9位用户的10个中间修订版本未显示）
第6行： 第6行：
 
|Dong Wang
 
|Dong Wang
 
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* Public talk in Chen Zhou
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* 2nd teacher training in Tsinghua middle school
 
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第17行： 第18行：
 
|Lantian Li
 
|Lantian Li
 
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* Check AI handbook high school (4/40)
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* Go on AI-Graph EN Chapter 4 (37/50)
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* Polish 2025 Daily Sign (5/12)
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* ICASSP Rebuttal
 
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第60行： 第64行：
  
 
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|Chen Chen
 
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|Xiaolou Li
 
|Xiaolou Li
 
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* Data Condition
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** CVS3: 2/4
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** GA data: ready for training
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* VSR-LLM Align with contrastive loss:
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** Loss drop great, but the output of Connector still strange, need to modify the function of align
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* thesis proposal
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* paper organization about VSR SSL method (for proposal)
 
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第84行： 第84行：
 
|Zehua Liu
 
|Zehua Liu
 
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*Label corruption still need explore
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*Inference Hyper-Parameter change
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**Iter-1（45.52%）-> Iter-2（44.60%）-> Iter-3 (44.30%)
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*Prepare start-term report and the draft of graduation thesis
 
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第106行： 第109行：
 
|Wan Lin
 
|Wan Lin
 
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* NS: all transformer
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** 5w spk + multi-enroll: EER 1.67%
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** variable-length training & adding spk
 
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第127行： 第132行：
  
 
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|Zhenyu Zhou
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|Xiaoxue Luo
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* production of 2025 Daily Sign(5/12)
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* production of 2025 Daily Sign(12/12)
 
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|Zhenyu Zhou
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*Prepare mid-term report and the draft of graduation thesis
 
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第176行： 第192行：
 
|Wenqiang Du
 
|Wenqiang Du
 
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* Project cooperation communication
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** Tencent-Contract discuss
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** dongxin- technical report about vpr
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** zhongchuan - local asr
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** Heeryuan - In bidding about RAG
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第187行： 第208行：
 
|Yang Wei
 
|Yang Wei
 
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* Train text enroll kws model with 7000h data with spec aug[https://z1et6d3xtb.feishu.cn/docx/WLLLd2zQvoiE78xfMhpcHejdnnd]
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* Experiment about inference rtf.[https://z1et6d3xtb.feishu.cn/docx/Sgo3dCvmqoovXOxvneYcBnXOnoh]
 
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第207行： 第229行：
 
|Turi
 
|Turi
 
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* Paper reading
 
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第225行： 第247行：
 
|Qi Qu
 
|Qi Qu
 
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* Finding ideal thresholds for `zh48+henan22` and `zh48+chongqing15` KWS models. `zh48+chongqing15` performs poorly and needs re-arranging word list and retraining.
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* NPU development/test environment setup: mr536 and v851se (new).
 
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2024年12月2日 (一) 10:58的最后版本

People This Week Next Week Task Tracking (DeadLine)
Dong Wang
  • Public talk in Chen Zhou
  • 2nd teacher training in Tsinghua middle school
Lantian Li
  • Check AI handbook high school (4/40)
  • Go on AI-Graph EN Chapter 4 (37/50)
  • Polish 2025 Daily Sign (5/12)
  • ICASSP Rebuttal
Ying Shi
  • Some personal stuff
  • Find some numerical issues of current conditional model (will be fixed in this week)
Zhenghai You
  • Huawei TSE IRA Demo[1]
Junming Yuan
  • Some varient experiments with MT-HuBERT[2]
  • get familiar with text-enroll experiment
Xiaolou Li
  • Data Condition
    • CVS3: 2/4
    • GA data: ready for training
  • VSR-LLM Align with contrastive loss:
    • Loss drop great, but the output of Connector still strange, need to modify the function of align
  • thesis proposal
  • paper organization about VSR SSL method (for proposal)
Zehua Liu
  • Label corruption still need explore
  • Inference Hyper-Parameter change
    • Iter-1（45.52%）-> Iter-2（44.60%）-> Iter-3 (44.30%)
  • Prepare start-term report and the draft of graduation thesis
Pengqi Li
Wan Lin
  • NS: all transformer
    • 5w spk + multi-enroll: EER 1.67%
    • variable-length training & adding spk
Tianhao Wang
  • Some test for out-of-domain text query gap [3]
  • thesis proposal
  • thesis proposal
Xiaoxue Luo
  • production of 2025 Daily Sign(5/12)
  • production of 2025 Daily Sign(12/12)
Zhenyu Zhou
  • Prepare mid-term report and the draft of graduation thesis
Junhui Chen
Jiaying Wang
Yu Zhang
  • thesis proposal
  • paper reading about Multi-Agent Collaboration
    • Cooperation in Different Roles
    • Competition in the Same Role
Wenqiang Du
  • Project cooperation communication
    • Tencent-Contract discuss
    • dongxin- technical report about vpr
    • zhongchuan - local asr
    • Heeryuan - In bidding about RAG
Yang Wei
  • Train text enroll kws model with 7000h data with spec aug[4]
  • Experiment about inference rtf.[5]
Lily
Turi
  • Paper reading
Yue Gu
  • ablation study about adaptation data, badcase analysis [6]
  • read several papers about synthetic data for data argumentation
Qi Qu
  • Finding ideal thresholds for `zh48+henan22` and `zh48+chongqing15` KWS models. `zh48+chongqing15` performs poorly and needs re-arranging word list and retraining.
  • NPU development/test environment setup: mr536 and v851se (new).
取自“http://cslt.org/mediawiki/index.php?title=2024-12-02&oldid=42591”