“2024-03-18”版本间的差异

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|Jiaying Wang
 
|Jiaying Wang
 
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* weekly report
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* PIT baseline: ConTasNet (finish tonight)
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* test whether the separation target is the closer one to the cohort embedding: the rate is around 0.5
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** confused about the efficiency of cohort
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** Further experiment:TasNet with minimal loss
 
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2024年3月18日 (一) 10:51的版本

People This Week Next Week Task Tracking (DeadLine)
Dong Wang
  • Interspeech 2024 paper refinement
  • Design/Discussion AI popular science
  • Conjecture for minmum loss training
Lantian Li
Ying Shi
  • Finish INTERSPEECH paper
  • Investigate random order SOT for multi-talker ASR task
  • 3-mix 0s offset test condition
    • DOM-SOT 20.51
    • PIT-SOT 23.26
    • random-order SOT 26.20
  • group work
Zhenghai You
  • Weekly report
  • Some evaluations about TSE speaker encoder
  • Huawei project (Phase 1st)
  • Some doubts about the paper due to the latest testing in minimum loss
  • Change the speakerbeam speaker encoder to frequency domain
  • Train a SID with a speakerbeam structure
Junming Yuan
  • Finish INTERSPEECH paper
  • Make the plan for the large vocabulary pretraining task.
    • Focus on the experimental details of the few-shot paper from Google.
    • Try to address the 3 questions:
      • How to change MT pretraining model structure?
      • How to train three strictly comparable pretraining models based on MT, Hubert, and wav2vec?
      • Why does Hubert+MT perform significantly better?
Chen Chen
  • Finish IS24 paper
  • Some documents for VTS X project
  • Proposal for next stage work on VSR/VTS
    • Focus on two task: 1) CNCVS2 dataset 2) Mandarin VSR Benchmark [1] on CNCVS1&2&CNVSRC
    • Aim at a solid benchmark with data/code/model
    • Perhaps a long journal paper
  • Conditional entropy analysis of VTS task
    • MFA is done
    • TODOs: feature/embedding extracting, clustering, discrete conditional entropy calculating
Xiaolou Li
Zehua Liu
  • Finish IS24
Pengqi Li
Wan Lin
Tianhao Wang
  • Finish INTERSPEECH paper
  • Code reorganization
Zhenyu Zhou
  • InterSpeech2024 submission
  • Code reorganization
  • Neuro scoring reviewing
Junhui Chen
Jiaying Wang
  • weekly report
  • PIT baseline: ConTasNet (finish tonight)
  • test whether the separation target is the closer one to the cohort embedding: the rate is around 0.5
    • confused about the efficiency of cohort
    • Further experiment:TasNet with minimal loss
Yu Zhang
  • Portfolio backtesting report
  • stock trade API
Wenqiang Du
  • Aibabel
    • Control Uyghur KWS model FA,but not get a good performance yet.
    • Continue test and update CN KWS model
Yang Wei
Lily
  • Paper reading
  • Prepare for overview paper
Turi
  • Data collection app[2]
  • Course works