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| | + | ** on both libri and wsj: training loss hard to reduce (around -3) and the corresponding test sisdr is positive |
| | + | * rewriting the code (preserving the original model) |
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| − | ** Baseline(ResNet34) training and NS training [https://z1et6d3xtb.feishu.cn/docx/BywjdkGvNou12sxQ4dAcxYa9noh?from=from_copylink]
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| | * VoxBlink1 | | * VoxBlink1 |
| | ** Data processing | | ** Data processing |
| − | ** Baseline(ResNet34 ASP) training and NS training [https://z1et6d3xtb.feishu.cn/docx/BywjdkGvNou12sxQ4dAcxYa9noh#Ro69dyERUoN0HvxOGMWcOJjrnuf] | + | ** Baseline(ResNet34) training and NS training [https://z1et6d3xtb.feishu.cn/docx/BywjdkGvNou12sxQ4dAcxYa9noh?from=from_copylink] |
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| − | |Jiaying Wang | + | |Junhui Chen |
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| − | * reproduce conditional chain code | + | * VoxBlink1 |
| − | ** on both libri and wsj: training loss hard to reduce (around -3) and the corresponding test sisdr is positive | + | ** Data processing |
| − | * rewriting the code (preserving the original model) | + | ** Baseline(ResNet34 ASP) training and NS training [https://z1et6d3xtb.feishu.cn/docx/BywjdkGvNou12sxQ4dAcxYa9noh#Ro69dyERUoN0HvxOGMWcOJjrnuf] |
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| People |
This Week |
Next Week |
Task Tracking (DeadLine)
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| Dong Wang
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- AI primary (middle-school) 1-6
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| Lantian Li
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- GPU status [1]
- AI primary
- High school handbook (30/40)
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- High school handbook (40/40)
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| Ying Shi
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| Zhenghai You
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| Jiaying Wang
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- reproduce conditional chain code
- on both libri and wsj: training loss hard to reduce (around -3) and the corresponding test sisdr is positive
- rewriting the code (preserving the original model)
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| Junming Yuan
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- Verified two parameters in Hubert pretraining config file that were confused with the original paper.[2]
- Confirmed that in the second iteration of pretraining, features should be extracted from the 6-th layer of the transformer, not the 9-th layer.
- in 175k step, result of 6-th layer: 71.55/9.39, result of 9-th layer: 37.31/16.72
- Basically confirmed the setting of the parameter 'untie_final_proj' for the two iterations of pretraining.
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| Xiaolou Li
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| Zehua Liu
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| Pengqi Li
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- Investigating Extremely Short-Utterance in speaker recognition[3]
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| Tianhao Wang
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- reproducing CLIPSep on two datasets: MUSIC and VGGSound [4]
- MUSIC: Text query: 10.06 SDR, Image query: 12.13 SDR
- VGGSound: Text query: 2.78 SDR, Image query: 5.01 SDR
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| Zhenyu Zhou
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| Wan Lin
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- VoxBlink1
- Data processing
- Baseline(ResNet34) training and NS training [5]
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| Junhui Chen
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- VoxBlink1
- Data processing
- Baseline(ResNet34 ASP) training and NS training [6]
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| Yu Zhang
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| Wenqiang Du
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- Complete Primary school handbook draft (45 + 8)
- Modify the format, expression, and distribution of knowledge points in the draft（40%）
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| Yang Wei
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| Lily
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| Turi
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| Yue Gu
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- modify the introduction
- complete the interspeech poster, and open source the paper code
- rest for two days, next I will focus on my new work
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| Qi Qu
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- KWS:
- zh48 test dataset to be updated: ~30 speakers in 3 locations.
- yue10 (Cantonese 10 keywords) train dataset to be updated: ~120 speakers verified, more to come.
- Try to find suitable keyword-wise thresholds based on Recall ~ FA relation.
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