“2024-10-28”版本间的差异

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|Ying Shi
 
|Ying Shi
 
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−
* revise the code about cohort-overlap asr
+
* revise the code about cohort-overlap asr [the training is in progress]
 
** Support arbitrary source mixing training  
 
** Support arbitrary source mixing training  
 
** Use the real hypothesis by Token error rate
 
** Use the real hypothesis by Token error rate

2024年10月28日 (一) 10:49的版本

People This Week Next Week Task Tracking (DeadLine)
Dong Wang
  • AI primary book done
Lantian Li
Ying Shi
  • revise the code about cohort-overlap asr [the training is in progress]
    • Support arbitrary source mixing training
    • Use the real hypothesis by Token error rate
Zhenghai You
  • Introduce more hard samples to improve model performance[1]
    • SPK-AUG with same length: There is an improvement, but the SI-SDR decreases when hard sample rate increases
    • Design more hard samples
Junming Yuan
  • The result of time-mask MT-HuBERT [2]
    • A sad news
Chen Chen
Xiaolou Li
Zehua Liu
  • Reading Papper about In-Context-Learning in ASR
  • Training model with Adaptive Time Mask
  • Try In-Context-Learning with only previous sentence[3]
  • VTS Project Report starts
Pengqi Li
  • Consistency of TAO and LayerCAM
    • Change TAO from input to final conv layer and obtain more consistency.(Aishell:0.93 in any model)
Wan Lin
Tianhao Wang
  • AudioSep (CLAP) 5-mix exps:
    • text-query: SDR=4.978, SI-SDR=1.972
    • audio-query: SDR=6.907, SI-SDR=5.058
    • This results with the loudness limitation
  • AudioSep (CLAP) without loudness limitation
  • Project things
Xiaoxue Luo
  • Comparative experiment between AudioSep and baseline system(CLIPSep)
  • Prepare the report
Zhenyu Zhou
  • reproduce 5-mix speech Separation results：
    • pit：2-mix：16.04 ；5-mix：6.87
    • conditional：5-mix：5.38（40 epoch）
Junhui Chen
Jiaying Wang
Yu Zhang
  • SocioDojo (still worse than Nasdaq100 baseline)
    • Change information sources, from the perspective of the report generated by LLM, more new information sources will be referenced.
    • Prompt Actuator to consider current cash ratio before investing (with out this, the asset ratio goes up to 100%, which leads to high risks, still running)
  • Read some papers about integrating time series into LLM
Wenqiang Du
  • Prepare data,code and environment for Pro.Mijiti
Yang Wei
  • Train text enroll KWS model with Aibabel training data. Not work.
Lily
Turi
Yue Gu
  • seek sugestions from other authors. Many suggestions are conflicting, so I'm try to figure out the reasons and fix these issues.
Qi Qu
  • KWS:
    • Text-enroll models exported to ONNX.
    • C/JNI libs built based on ONNX models and ready for on-device test.
取自“http://index.cslt.org/mediawiki/index.php?title=2024-10-28&oldid=42370”