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| 第227行： |
第227行： |
| | |Qi Qu | | |Qi Qu |
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| − | * | + | * Adding modules to codebase: converting models (text-enroll models, CED models and classifiers) to NPU format. |
| | + | * Some debugging on mr536 and v85se. |
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| People |
This Week |
Next Week |
Task Tracking (DeadLine)
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| Dong Wang
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- Polish AI college version
- Two talks in Guangxi
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| Lantian Li
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- CSTR report on TSE and USS.
- Dissertation reviews
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| Ying Shi
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| Zhenghai You
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- Some tests of Huawei project
- Writing the report of Huawei project
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| Junming Yuan
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- Make Jiaoyubu's AI lesson PPTs with Qiang bro
- Add 3-mixed test results under 2-mix finetuning setting and revise CN version of MT-HuBERT paper
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| Xiaolou Li
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- Write GA doc (test report and mid term report)
- Prepare the presentation PPT
- Improve the VTS demo system
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| Zehua Liu
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- Write GA doc (test report and mid term report)
- Prepare the presentation PPT
- Improve the VTS demo system
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| Pengqi Li
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- Make Jiaoyubu's AI lesson PPTs with Qiang bro
- Review my research.
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| Wan Lin
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- Finish model training, only some test tasks left
- Write paper: finish intro, related, method
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| Tianhao Wang
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- Huawei huohua model training
- demo
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| Xiaoxue Luo
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- compared CED topk labels with ground truth labels, most CED labels are parent labels of ground truth(eg.ground truth: Male speech,man speaking; CED label: Speech)
- adjust the order of separating audio from low to high probability, it means that our method is effective(SDR: our method: 12.2182; reversed: 11.8793)
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| Zhenyu Zhou
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| Junhui Chen
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- Continue to write NS paper (soon discuss with LW)
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| Jiaying Wang
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- finish linear ASR module training：ctc loss converge at around 60, test loss 115.4
- testing letter error rate
- Network+ presentation preparation with Qiang bro
- weekly report
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| Yu Zhang
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- add reflection and memory mechanism based on market feedback (still fine-tuning prompt)
- try other policy fusion method, no significant improvement.
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| Wenqiang Du
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- Jiaoyubu's AI lesson（10/10）with Junming and Pengqi
- Some tasks about company
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| Yang Wei
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- Test backend ASR model with AIBabel keyword data.
- Review the mispronunciation detection project.
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| Turi
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- Filled some thesis forms and paper reading
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| Yue Gu
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- reproduce some exps about hotword
- write the method part (30%)
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| Qi Qu
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- Adding modules to codebase: converting models (text-enroll models, CED models and classifiers) to NPU format.
- Some debugging on mr536 and v85se.
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