“2024-04-15”版本间的差异

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** Tested with EfficientNetB{2,4,6,8}
 
** Tested with EfficientNetB{2,4,6,8}
 
** Service to be implemented with EfficientNetB6 (preview)
 
** Service to be implemented with EfficientNetB6 (preview)
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* complete the experiments of contextual ASR
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* complete the pseudocodes of group stage and bias-phrase decoding lattice
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* read one paper
 
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2024年4月15日 (一) 10:38的版本

People This Week Next Week Task Tracking (DeadLine)
Dong Wang
  • Interspeech review
  • AI primary education design
  • <Illustraitver AI> slides refinement
Lantian Li
Ying Shi
Zhenghai You
  • Retrain a SpEx+ model more suitable for online
  • Reflect on cohort and reorganized document
  • paper reading
Junming Yuan
  • prepare materials of live broadcast
  • paper reading
  • got sick
Chen Chen
Xiaolou Li
Zehua Liu
  • auxiliary loss exp[1]
  • crop_size exp(still training)
  • read papper
  • reproduce other architecture
Pengqi Li
  • speech XAI review v1[2]
  • polished poster
  • live broadcast
  • ICASSP review
Wan Lin
  • Finish graduation paper
  • Explore multi-speaker training in NS (how to get batter result in all condition)
    • use wespeaker toolkit
    • effect of time of training sample
    • inherit hard speaker sample
    • add channel-time attention in ResNet to get enroll-aware test feature
Tianhao Wang
  • EA-ASP exps
    • aligned toolkit (wespeaker To sunine), failed. we will align to wespeaker
    • aligned training data (weak overlap To strong overlap)
      • concat and weak_overlap worse, overlap and mix better compared to previous
      • NS arch. has advantages under mix, but non under other tests compared to EA-ASP
  • read paper
  • reproduce SpEx+ in TSV
Zhenyu Zhou
Junhui Chen
Jiaying Wang
  • re-organized document 0025[3]
  • SS_based: Conv-Tasnet with one fixed cohort(still training)[4]
  • paper reading
Yu Zhang
  • SAC model training and backtesting [5]
  • financial quantile work pipeline finish
  • add more data to pipeline (more benchmark and more training testing data range)
  • append financial-pipeline design and implement detail doc
  • AutoML for stock return regression
Wenqiang Du
  • Efficient-B6 pretrain model training
  • hard negative training
    • FA data is being collected
Yang Wei
  • Children mispronunciation detection
    • Analyze and check the baseline model
  • Huilan
    • ASR service bug fix and update
Lily
  • Paper reading [6]
  • Assisted to prepare AI graph course materials and PPTs
  • Prepare for AI radiance live broadcast
Turi
  • Data collection App[7]
    • Tested the app and Fixed some bugs
  • Start Recording
Qi Qu
  • Server-side KWS:
    • Tested with EfficientNetB{2,4,6,8}
    • Service to be implemented with EfficientNetB6 (preview)
Yue Gu
  • complete the experiments of contextual ASR
  • complete the pseudocodes of group stage and bias-phrase decoding lattice
  • read one paper
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