| People |
This Week |
Next Week |
Task Tracking (DeadLine)
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| Dong Wang
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- English version of the AI handbook - middle/high school almost done
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| Lantian Li
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- Final review of my MLA book (3/10)
- MoE daily work
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| Wenqiang Du
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- Check AI course PPT(4/14)
- Completed AI100 question task and will be uploaded to the platform this month
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| Yang Wei
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- Some additional result analysis and some revisions on manuscript according to the reviewer' comments. [1][2]
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| Ying Shi
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| Pengqi Li
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- Draft Paper: The framework and core content are complete.
- AI Handbook: Checking and verifying references.
- Winter Camp Preparation: Preparing materials for the Tsinghua University Middle School AI Winter Camp.
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| Junming Yuan
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- Aug-MT-HuBERT:
- Fixed the pre-training to 100K steps, compared 3 noise ratios（50%, 80%, and 100%）and 2 different SNR sampling strategies([-3, 3] uniform / [0, 10] Gauss).
- Best setting, PR performance(PER): 8.12 -> 8.08, ASR performance(WER): 9.22 -> 9.07
- There is still around 3% gap compared to HuBERT.
- SS adaptation(SI-SDRi):
- Cocktail-HuBERT(14.76) > MT-HuBERT(13.93) > WavLM(13.83) > ConvTasNet(10.39)
- Draft Paper( CN version almost done)
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| Yu Zhang
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- GPU Util [3]
- working on the big assignment and preparing for the final exam.
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| Junhui Chen
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| Xiaolou Li
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- Prepared applications for 4 CDT programmes
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| Jiaying Wang
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- spk order separation training
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| Tianhao Wang
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- additional experiments for ChainSep [4]
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| Xiaoxue Luo
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- 2-5mix attractor-based USS model for Huawei project
- SI-SDR : 2mix: 4.725， 3mix: 0.866， 4mix: -1.155， 5mix: -2.709
- design a better solution for Huawei project
- multi-head separation (two groups: speakers and events)
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| Yue Gu
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| Lily
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| Bochao Hu
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- P2S wer: 45%.data:20% GT 20% real seq 60% synthetic seq. llm can't correct with high per(> 30%)
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| Hongcheng Zhang
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- finish the main code of ASU-LLM (CLAP + HuBERT)。The core architecture consists of a dual-stream encoder combing CLAP and Audio Hubert,integrated with LLaMA
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