“2024-08-26”版本间的差异

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|Ying Shi
 
|Ying Shi
 
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* Fenyinta stuff
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* reproduce cohort-SOT overlap ASR and some analysis
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* Text enroll keywords spotting intermediate PIT-SOT CTC + high layer cross-attention is in progress  [https://z1et6d3xtb.feishu.cn/docx/DI3UdF496ojxCQxTqUycsjDQnxf?from=from_copylink here]
 
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|Xiaolou Li
 
|Xiaolou Li
 
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* LLM long context test
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* Poster for IS24
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* Paper reading
 
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* 9.20(one month)
 
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|Jiaying Wang
 
|Jiaying Wang
 
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* re-write conditional chain code
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* re-write conditional chain code(can be finished this week)
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* check wsj data
  
 
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|Yang Wei
 
|Yang Wei
 
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* Check the badcase of KWS model test.
 
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* write the introduction
 
* write the introduction
 
* test the adaptation model on the same accent data:[https://www.yuque.com/g/shibeiing/angax2/efpdhqvsxdi4phua/collaborator/join?token=ysvAeigXC9KFi4CF&source=doc_collaborator]
 
* test the adaptation model on the same accent data:[https://www.yuque.com/g/shibeiing/angax2/efpdhqvsxdi4phua/collaborator/join?token=ysvAeigXC9KFi4CF&source=doc_collaborator]
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(got sick today)
 
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|Qi Qu
 
|Qi Qu
 
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* KWS:
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** zh48 test dataset updated: 29 speakers in 3 locations, ~600 utterances per keyword.
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** Recall ~ FA relations plotted.
 
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2024年8月26日 (一) 11:03的最后版本

People This Week Next Week Task Tracking (DeadLine)
Dong Wang
  • Primary school book (17)
  • College AI education
Lantian Li
  • GPU status [1]
  • AI primary
    • High school handbook (40/40)
Ying Shi
  • Fenyinta stuff
  • reproduce cohort-SOT overlap ASR and some analysis
  • Text enroll keywords spotting intermediate PIT-SOT CTC + high layer cross-attention is in progress here
Zhenghai You
  • Speaker Augument: Completed experiments in Libri2mix, Low SISDR testset lower speaker confusion rate
  • ExFormer: Always inferior to the SOTA[2]
Junming Yuan
  • Confirmed that the performance gap of the 10% is determined by the impact of GPUs[3].
    • To fully reproduce the official model, it would take approximately 32 days.
  • Investigate how to train Hubert with Mix-speech (in progress)
Xiaolou Li
  • LLM long context test
  • Poster for IS24
  • Paper reading
Zehua Liu
  • CNVSRC 2024 Website
  • Data transfer to HUAWEI
  • LLM in Chinese VSR(In-context-learning)
Pengqi Li
  • Extend Proposal for 'HOW PHONEMES CONTRIBUTE TO DEEP SPEAKER MODELS?'[4]
    • Reviewing code, paper.
    • Analyzing di-phones in Audio-Mnist.
    • Start exp with TIMIT dataset.
  • 9.20(one month)
Wan Lin
  • Neural Scoring: vox2+voxblink1 [5]
Tianhao Wang
  • AudioSep reproducing
  • IS24 poster
Zhenyu Zhou
  • Some thinking about onnx quantization[6]
Junhui Chen
  • Neural Scoring:
    • Vox2+Voxblink-clean test[7]
Jiaying Wang
  • re-write conditional chain code(can be finished this week)
  • check wsj data
Yu Zhang
  • AED engineering problem assist
  • Prepare for report
Wenqiang Du
  • Complete the unified format and recheck of Primary school handbook
  • Write middle school handbook(29-41)
  • Training Chinese and Cantonese KWS model
Yang Wei
  • Check the badcase of KWS model test.
Lily
Turi
  • Added more sections to the draft paper
    • Need to refine and do more experiments
Yue Gu
  • write the introduction
  • test the adaptation model on the same accent data:[8]

(got sick today)

Qi Qu
  • KWS:
    • zh48 test dataset updated: 29 speakers in 3 locations, ~600 utterances per keyword.
    • Recall ~ FA relations plotted.