“2025-03-17”版本间的差异

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(15位用户的20个中间修订版本未显示)
第18行: 第18行:
 
|Lantian Li
 
|Lantian Li
 
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* Submit of the AI-Graph EN version
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* Review Master theses
 
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第29行: 第30行:
 
|Ying Shi
 
|Ying Shi
 
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* thesis
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* some school-related stuff
 
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第41行: 第43行:
 
|Zhenghai You
 
|Zhenghai You
 
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* Complete the training and experimentation of the TSE-IRA model[https://z1et6d3xtb.feishu.cn/wiki/OXubwl2fIip91vkYsgMc1duhnLd] for Huawei, and will write the report
 
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第51行: 第53行:
 
|Junming Yuan
 
|Junming Yuan
 
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*  
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* prepare report
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* double-check middle-school AI handbook(1/7)
 
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+
* write paper
 +
* double-check middle-school AI handbook
 +
* AI practice handbook design of primary school and middle school
 
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第62行: 第67行:
 
|Xiaolou Li
 
|Xiaolou Li
 
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* Writing NSFC document
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* Find solutions for the low training speed with hybrid data disk
 
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第73行: 第79行:
 
|Zehua Liu
 
|Zehua Liu
 
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*Writing NFSC document
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*Reading VTS paper
 
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第84行: 第91行:
 
|Pengqi Li
 
|Pengqi Li
 
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*  
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* Prepare the AI course for Tsinghua University middle School.
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* Add references to the middle handbook(Done)
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* Check middle handbook(1/3)
 
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第95行: 第104行:
 
|Wan Lin
 
|Wan Lin
 
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*  
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* train ns(multi-enroll) for voxblink1+voxceleb2: perform better than before, but still worse than vc2-only
 +
* retrain multi-scenario ns(multi-enroll) model: consistently better than before now [https://z1et6d3xtb.feishu.cn/docx/MxBNdPbLao0tsoxkBVCcUgUoneh?from=from_copylink]
 +
* run ablation experiments: w/o multi-enroll/multi-head/two encoder
 
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*
 
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第106行: 第117行:
 
|Tianhao Wang
 
|Tianhao Wang
 
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*  
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* sound sep subset training & testing
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* huawei interview
 +
* professor Guo's project investigation
 
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*
 
*
第117行: 第130行:
 
|Xiaoxue Luo
 
|Xiaoxue Luo
 
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*  
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* Sound separation
 +
** train AudioSep on subset data and evaluate it with our testing dataset
 +
** read a paper about USS, try to test this model using our test set firstly(adjusting code in progress)
 
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*
 
*
第128行: 第143行:
 
|Zhenyu Zhou
 
|Zhenyu Zhou
 
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* Revise graduation thesis
 
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第151行: 第166行:
 
|Jiaying Wang
 
|Jiaying Wang
 
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*
+
* re-design the network structure[https://z1et6d3xtb.feishu.cn/docx/TUHldiaoQoYBqux7JEhcaCXenzh]
 +
** network without cross attention is already quite large and requires more than 2 GPUs for training,need to be reduced
 
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*
 
*
第162行: 第178行:
 
|Yu Zhang
 
|Yu Zhang
 
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*  
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* Some software structure design and function time flow design in Royal Flush (for external robot project)
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* AED stream inference and score smooth window size experiment
 
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*
 
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第173行: 第190行:
 
|Wenqiang Du
 
|Wenqiang Du
 
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*  
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* Check Primary handbook V3.1
 +
*  Check middle  handbook 
 +
*  We have Dragon05 (A6000 * 6)
 
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*
第184行: 第203行:
 
|Yang Wei
 
|Yang Wei
 
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*  
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* Text enroll kws adaptation experiment on cross lingual data. (not work. trying it with more complex adaptation layer)
 
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*
 
*
第194行: 第213行:
 
|Turi
 
|Turi
 
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*  
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* Prepared ppt and poster for ICASSP2025
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* Did presentation video and submitted with poster
 
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*  
 
*  
第211行: 第231行:
 
|Qi Qu
 
|Qi Qu
 
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* Android demo of Text-enroll KWS model.
 
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2025年3月17日 (一) 10:58的最后版本

People This Week Next Week Task Tracking (DeadLine)
Dong Wang
  • AI handbook refinment for the college version.
Lantian Li
  • Submit of the AI-Graph EN version
  • Review Master theses
Ying Shi
  • thesis
  • some school-related stuff
Zhenghai You
  • Complete the training and experimentation of the TSE-IRA model[1] for Huawei, and will write the report
Junming Yuan
  • prepare report
  • double-check middle-school AI handbook(1/7)
  • write paper
  • double-check middle-school AI handbook
  • AI practice handbook design of primary school and middle school
Xiaolou Li
  • Writing NSFC document
  • Find solutions for the low training speed with hybrid data disk
Zehua Liu
  • Writing NFSC document
  • Reading VTS paper
Pengqi Li
  • Prepare the AI course for Tsinghua University middle School.
  • Add references to the middle handbook(Done)
  • Check middle handbook(1/3)
Wan Lin
  • train ns(multi-enroll) for voxblink1+voxceleb2: perform better than before, but still worse than vc2-only
  • retrain multi-scenario ns(multi-enroll) model: consistently better than before now [2]
  • run ablation experiments: w/o multi-enroll/multi-head/two encoder
Tianhao Wang
  • sound sep subset training & testing
  • huawei interview
  • professor Guo's project investigation
Xiaoxue Luo
  • Sound separation
    • train AudioSep on subset data and evaluate it with our testing dataset
    • read a paper about USS, try to test this model using our test set firstly(adjusting code in progress)
Zhenyu Zhou
  • Revise graduation thesis
Junhui Chen
  • Finished diarization test in vox-o
    • continue in vox-e
Jiaying Wang
  • re-design the network structure[3]
    • network without cross attention is already quite large and requires more than 2 GPUs for training,need to be reduced
Yu Zhang
  • Some software structure design and function time flow design in Royal Flush (for external robot project)
  • AED stream inference and score smooth window size experiment
Wenqiang Du
  • Check Primary handbook V3.1
  • Check middle handbook
  • We have Dragon05 (A6000 * 6)
Yang Wei
  • Text enroll kws adaptation experiment on cross lingual data. (not work. trying it with more complex adaptation layer)
Turi
  • Prepared ppt and poster for ICASSP2025
  • Did presentation video and submitted with poster
Yue Gu
  • synthesize 100h for each target spk and use KL loss as the regular term, the CER of target speakers reduce 10%.
Qi Qu
  • Android demo of Text-enroll KWS model.