“2022-09-26”版本间的差异

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(11位用户的22个中间修订版本未显示)
第5行: 第5行:
 
|Dong Wang
 
|Dong Wang
 
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* Review low-resource ASR
 
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*
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* Complete the review
 
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+
 
 
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第16行: 第16行:
 
|Lantian Li
 
|Lantian Li
 
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*
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* Proposals on
 +
** music generation
 +
** binary speaker embedding
 +
** acoustic-aware learning
 
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*  
+
* Hard trials paper...
 
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*   
 
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第27行: 第30行:
 
|Ying Shi
 
|Ying Shi
 
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*  
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* computational efficiency between fncmd and transformer kws
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* PhD research proposal
 
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* finish PhD research proposal
 
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*   
 
*   
第38行: 第42行:
 
|Chen Chen
 
|Chen Chen
 
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*  
+
* Finish draft
 +
* pre-process CMLR data
 
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*  
+
* Train ASR model on GRID and test WER
 +
* Train VTS model on CMLR single spk
 +
* Train VCA-GAN
 +
* Prepare weekly-reading report
 
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*   
 
*   
第49行: 第57行:
 
|Pengqi Li
 
|Pengqi Li
 
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*
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* summary of mask-based method [https://obwanu1cox.feishu.cn/docx/doxcnori1nTh0pRUDO5DXcdalSh Outline]
 
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*
 
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第61行: 第69行:
 
|Zixi Yan
 
|Zixi Yan
 
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*
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* Revise paper
 +
* make a resume
 
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*
 
*
第67行: 第76行:
 
*   
 
*   
 
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|Sirui Li
 
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*
 
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|Haoyu Jiang
 
|Haoyu Jiang
 
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*
+
* weekly report
 +
* Prepare the environment of Wenet
 
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*
 
*
第104行: 第103行:
 
|Renmiao Chen
 
|Renmiao Chen
 
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*  
+
* Finish data collection
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* Finish CLLR score fusion
 +
* Try the maskFace [http://index.cslt.org/mediawiki/images/5/5c/220926-CRM.pdf pdf]
 
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*  
+
* Finish tools for get LiRAVD
 +
* Extract embedding from LiRAVD and get results
 +
* Complete the remaining benchmarks
 
||
 
||
 
*   
 
*   
第113行: 第116行:
 
|Wenqiang Du
 
|Wenqiang Du
 
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*
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* Some project cooperation
 
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*
 
*
第125行: 第128行:
 
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*
 
*
 +
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 +
 +
|-
 +
|-
 +
|Tianhao Wang
 +
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 +
* postgraduate recommendation
 +
* time-aligned mask
 +
||
 +
* finish and summarize time-aligned mask
 +
||
 +
 +
|-
 +
|Xipin Wei
 +
||
 +
* Read the music generation documents
 +
* The scheme of mutil-track-instruments
 +
||
 +
* The scheme of mutil-track-instruments
 
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*   
 
*   
 
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2022年9月26日 (一) 11:01的最后版本

People This Week Next Week Task Tracking (DeadLine)
Dong Wang
  • Review low-resource ASR
  • Complete the review
Lantian Li
  • Proposals on
    • music generation
    • binary speaker embedding
    • acoustic-aware learning
  • Hard trials paper...
Ying Shi
  • computational efficiency between fncmd and transformer kws
  • PhD research proposal
  • finish PhD research proposal
Chen Chen
  • Finish draft
  • pre-process CMLR data
  • Train ASR model on GRID and test WER
  • Train VTS model on CMLR single spk
  • Train VCA-GAN
  • Prepare weekly-reading report
Pengqi Li
  • summary of mask-based method Outline
Zixi Yan
  • Revise paper
  • make a resume
Haoyu Jiang
  • weekly report
  • Prepare the environment of Wenet
Ruihai Hou
Renmiao Chen
  • Finish data collection
  • Finish CLLR score fusion
  • Try the maskFace pdf
  • Finish tools for get LiRAVD
  • Extract embedding from LiRAVD and get results
  • Complete the remaining benchmarks
Wenqiang Du
  • Some project cooperation
Wan Lin
Tianhao Wang
  • postgraduate recommendation
  • time-aligned mask
  • finish and summarize time-aligned mask
Xipin Wei
  • Read the music generation documents
  • The scheme of mutil-track-instruments
  • The scheme of mutil-track-instruments