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| 第83行： |
第83行： |
| | |Chen Chen | | |Chen Chen |
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| − | * | + | * graduate |
| | + | * entropy (with avhubert/hubert for LRS3/GRID) |
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| − | * | + | * finish ISCSLP paper |
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| People |
This Week |
Next Week |
Task Tracking (DeadLine)
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| Dong Wang
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- A trial talk in Retired Professor Association of THU.
- Check Aigraph slides
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| Lantian Li
|
- GPU status [1]
- Projects
- AED -> model miniaturization/streaming
- TSE -> 1st phase delivery (this week)
- VSR -> no progress
- Finance -> no progress
- Papers
- AI graph
- Slides checking (10/50)
- High school handbook (2/40)
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| Ying Shi
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- Text enroll Keyword Spotting
- Training with sufficient data augmentation [failed]
- Cohort Conditional Chain Overlap ASR
- Fix the bug about the positional embedding of Condition, the performance is still not good
- Review several NC paper
|
- Text enroll Keyword Spotting
- Cohort Conditional Chain Overlap ASR
- Check the SID performance of the current speaker embedding model on the training dataset
- Reproduce the previous Cohort-SOT methods on the training dataset
- Finish the SPL response
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| Zhenghai You
|
- Complete the project deliverables
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| Junming Yuan
|
- find the bug in SSL model finetuning experiment with multi-lingual
- double check result in [2]
- The results need check again.
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| Chen Chen
|
- graduate
- entropy (with avhubert/hubert for LRS3/GRID)
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| Xiaolou Li
|
- Some exps on Bimamba (parameters search) [3]
- Paper reading
- MLLM survey, pre-train, fine-tune and modality alignment
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| Zehua Liu
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- VSP-LLM Reproduce（LRS3(30h) wer:36.32 > wer: 29.2）[4]
- still need work on the code
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| Pengqi Li
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| Wan Lin
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- Neural Scoring
- trials test: vox1-e, vox1-h
- cn: ns(all-genres and 3-genres fine-tuning)
- variable-chunk training(2-10s):
training, looks similar to the results of 4/6s
- weekly report
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| Tianhao Wang
|
- Neural Scoring [5]:
- vox: vox1-e, vox1-h test [6]
- cn: three genres fine-tuning: resnet and ns, 2s and 4s
- weekly report
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| Zhenyu Zhou
|
- Huawei Project Submission
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| Junhui Chen
|
- Neural Scoring [7]:
- vox: vox1-e, vox1-h test [8]
- vox: one transformer encoder layer training
- cn: three genres fine-tuning: resnet and ns, 2s and 4s
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|
| Jiaying Wang
|
- Preliminary validation: cohort works[9]
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| Yu Zhang
|
- Finance
- Data Collection (2015 - 2019 HS300 stocks)
- AED
- 8k 2s CNN model training and Window inference code
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|
|
| Wenqiang Du
|
- Quantified the kws model of Aibabel
- Training dialect models for AIbabel（ Uyghur language）
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- Train a joint model for Chinese, Uyghur, and Kazakh languages
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|
| Yang Wei
|
- AIbabel
- Learn to train and test KWS model
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| Lily
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- Assisted with design of AI courses for primary, high school
- Some chores about 'AIradiance'
- Prepare application for Beijing Science and Technology Progress Award
- Live broadcast
- Prepare the content for the daily sign poster for July, August
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| Turi
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- Thesis Proposal Defense
- Data Collection
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| Yue Gu
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- Prepare the live content
- writing paper
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| Qi Qu
|
- AED:
- CED + Linear: c/jni/python lib development and test.
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- AED:
- CED: Linear to be trained on data.
- On-device demo.
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