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第6行: |
| |Dong Wang | | |Dong Wang |
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− | * | + | * Presentation for Chongqing event |
| + | * NMI revision submitted |
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People |
This Week |
Next Week |
Task Tracking (DeadLine)
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Dong Wang
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- Presentation for Chongqing event
- NMI revision submitted
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Lantian Li
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- GPU status [1]
- Projects
- AED -> Miniaturization (TDNN, PARM 166K, AUC 0.93)
- TSE -> Streaming test and quantization
- VSR -> CNCVS3: 34h
- ASV -> A new project
- Finance -> Fix data preparing bug
- Research
- NeuralScoring: Exps done.
- TSE: Reproducing DPRNN-IRA.
- VSR-LLM: ICL exps.
- SoundFilter
- AI graph
- Slides checking (23/50)
- High school handbook (3/40)
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- High school handbook (15/40)
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Ying Shi
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Zhenghai You
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Junming Yuan
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- Start Hubert pretraining experiment using fairseq
- fix some bug and start pretraining on our Libri-keyword corpus.
- Beginner's Guide for training Hubert with fairseq:[2]
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Xiaolou Li
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- VSP-LLM code(help by Zehua)
- Llama Factory Fail
- paper reading and report
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Zehua Liu
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- ICL code
- VSP-LLM reproduce success
- read paper and share
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Pengqi Li
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Wan Lin
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- Neural Scoring: musan exp & paper writing & reference survey
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Tianhao Wang
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- Neural Scoring: musan exps
- New task investigation: Sound Filter
- project
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Zhenyu Zhou
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Junhui Chen
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Jiaying Wang
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- wsj dataset:
- 2mix baseline(done)
- 2mix + cohort:poor performance, need to test the EER of wsj dataset
- librimix dataset:
- 3mix baseline(done)
- 3mix + cohort: overfit and loss>0 --> plan to see transformer attention map
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- use condition chain frame on cohort
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Yu Zhang
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- TDNN 200k Training[3]
- R2_SAC still debugging
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Wenqiang Du
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- Continuously upgrade the model according to the plan
- primary school handbook (7/46)
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Yang Wei
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Lily
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- Thesis
- Daily Work at AIRadiance
- Live Broadcast
- Prepare Lenovo's Lecture
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Turi
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- Data collection
- Almost finished, 54K utterence (~100+hrs)
- Experiment
- Trained standard conformer on 65hrs of data using wenet. Loss normally decreases[4]
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- Add recently collected data and train
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Yue Gu
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- fix bugs
- read several recently published papers, then complete draft of the abstract and introduction. (6.5/9)
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Qi Qu
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- AED:
- CED-based classifier: libs and android demo (running and collecting FAs).
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