“2024-10-14”版本间的差异

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|Wan Lin
 
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*NS poster
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2024年10月14日 (一) 10:59的版本

People This Week Next Week Task Tracking (DeadLine)
Dong Wang
  • AI handbook high-education version, experiment booklet
  • Check AI primary school handbook (1-20)
Lantian Li
  • AI-Graph EN (20/50)
  • Prepare CSTR intro report
Ying Shi
  • Finish Text enroll keywords spotting code & document and deliver to Wei & Du
  • Cohort Overlap ASR code v0.0
    • code has finished and training has been done
  • Cohort Speech separation code v0.0
    • code has finished training is in progress
  • here
Zhenghai You
  • Exploring the role of speaker encoder in TSE and generality of SPK-AUG[1]
Junming Yuan
  • MT-Hubert exp[2]:
    • codebook set + infoNCE ---> FC+softmax+CE / FC+sigmoid+BCE
      • To reduce the learning rate can work.
    • verified the feat-mask MT-Hubert with different lr
    • time-mask MT-Hubert verification (in progress)
Chen Chen
Xiaolou Li
  • AV-HuBERT discrete unit training (wer: ↓1.5-3%)
    • rethink how to prove the advantage or disadvantage of discrete unit?
  • Dense connector experiments (in training)
  • Double check the data of existing 3000h data in CVS2
  • Paper reading (discrete unit, VTS)
  • Design a experiment to explain the performance of discrete unit
  • Finish data double check
  • Try to establish a simple VTS system based on our VSR system
Zehua Liu
  • Av-Hubert(Frozen) as Encoder performe very bad(cer:80%)[3]
    • after finetune maybe better ,but still bad
  • Qwen-14B perform better(47%) than Qwen-7B(50%)
  • Finish In-Context-Learning code and is training
    • maybe i will get result very soon
  • verify collected data with XiaoLou
  • finish VTS data Acceptance report
Pengqi Li
  • Evaluate TAO and LayerCAM(verification) reliability.
    • Exploring the Consistency of TAO and LayerCAM Results on different models and datasets.
Wan Lin
  • NS poster
  • NS
    • data preparing and processing
    • adjust the training code
Tianhao Wang
  • CLIPSep exps for 2-mix and 5-mix [4]
    • 2-mix(whole vggsound, 300 classes): SDR-mix = -1.1748, SDR-separate = 5.0145
    • 5-mix(50 classes of vggsound): SDR-mix = -11.4529, SDR-separate = -0.4764
Xiaoxue Luo
  • Paper reading about sound separation
  • AudioSep reproduction
    • Training time is too long -> replace with a small dataset(in training)
Zhenyu Zhou
  • Model quantization version2
  • Multi-talker mix data preparation
Junhui Chen
  • Prepare vb2 data
    • Too many utterances for training (out of memory), thinking a smart way to divide them.
Jiaying Wang
Yu Zhang
  • SocioDojo Llama version
    • news integration is adjusted once every 12 hours
    • wikipedia & google search is banned
Wenqiang Du
  • Check the data from past training models and update the KWS model again(Model testing)
    • Chinese, Cantonese, Minnan, Haining and Uyghur
Yang Wei
  • Train text enroll KWS model with updated code (in progress)
Lily
Turi
  • Whisper model finetuning[5]
Yue Gu
  • revise the TASLP paper
  • read several papers about accent and prosody
Qi Qu
  • AED: classifiers retrained w/ new method (suppression on negative stimuli) and improvement attested.