“2021-11-15”版本间的差异

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(8位用户的8个中间修订版本未显示)
第5行: 第5行:
 
|Dong Wang
 
|Dong Wang
 
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* Spoof paper almost done
 
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* Spoof paper cleaning
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* Hard trials paper
 
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第28行: 第29行:
 
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* Complete hard trials paper v1.
 
* Complete hard trials paper v1.
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* Go on preparing my defence.
 
* Go on preparing my defence.
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第38行: 第39行:
 
|Ying Shi
 
|Ying Shi
 
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* make a comparison  between fncmd with new methods
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* find some cross-modality methods(Cross modality attention)
 
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* Implement Cross modality attention
 
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第49行: 第51行:
 
|Haoran Sun
 
|Haoran Sun
 
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* speaker and robustness test for CycleFlow-spk
 
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* some improvement
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* some other exploration for the model
 
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第71行: 第74行:
 
|Pengqi Li
 
|Pengqi Li
 
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*  
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* reproduce about CAM(class activation map)
 
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第92行: 第95行:
 
|Weida Liang
 
|Weida Liang
 
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* Renew the project website and upload relevant speech sequences
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* Draw various loss curves
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* Prepare test data for content-relevant tests
 
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* Quantitave test
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* Prepare test data for speaker separation tests
 
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第113行: 第119行:
 
|Sirui Li
 
|Sirui Li
 
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*  
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* Compare the training process of TIMIT and Tibetan
 
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* Fine-tune the Tibetan wav2vec model
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* Prepare the thesis opening report
 
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第124行: 第131行:
 
|Haoyu Jiang
 
|Haoyu Jiang
 
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* Data set filtering based on face recognition
 
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第135行: 第142行:
 
|Ruihai Hou
 
|Ruihai Hou
 
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* Top 1 filtering based on face recognition
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* Prepare enrollment dataset for Top 1 filtering
 
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2021年11月22日 (一) 02:06的最后版本

People This Week Next Week Task Tracking (DeadLine)
Dong Wang
  • Spoof paper almost done
  • Spoof paper cleaning
  • Hard trials paper
Yunqi Cai
  • Completed THS2021 data preprocessing, image feature extraction, and baseline
Lantian Li
  • Complete hard trials paper v1.
  • Go on preparing my defence.
Ying Shi
  • make a comparison between fncmd with new methods
  • find some cross-modality methods(Cross modality attention)
  • Implement Cross modality attention
Haoran Sun
  • speaker and robustness test for CycleFlow-spk
  • some improvement
  • some other exploration for the model
Chen Chen
Pengqi Li
  • reproduce about CAM(class activation map)
Qingyang Zhu
Weida Liang
  • Renew the project website and upload relevant speech sequences
  • Draw various loss curves
  • Prepare test data for content-relevant tests
  • Quantitave test
  • Prepare test data for speaker separation tests
Zixi Yan
  • Modify wav2vec-u gan network code and output intermediate results
  • Training wav2vec2 model
Sirui Li
  • Compare the training process of TIMIT and Tibetan
  • Fine-tune the Tibetan wav2vec model
  • Prepare the thesis opening report
Haoyu Jiang
  • Data set filtering based on face recognition
Ruihai Hou
  • Top 1 filtering based on face recognition
  • Prepare enrollment dataset for Top 1 filtering
Renmiao Chen