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| 第6行： |
第6行： |
| | |Dong Wang | | |Dong Wang |
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| − | * | + | * Presentation for Chongqing event |
| | + | * NMI revision submitted |
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| | * | | * |
| 第43行： |
第44行： |
| | |Ying Shi | | |Ying Shi |
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| − | * | + | * Text enroll keyword spotting U-net |
| | + | ** Current AUC(U-transformer-net): 0.98 |
| | + | ** Previous AUC(Normal transformer + keyword decoder): 0.94 |
| | + | * More test for next HUAWEI project (TC-ASR) |
| | + | ** aishell-clean-test KCS-CER: 9.34% |
| | + | ** aishell-2mix-target-0dB-SNR KCS-CER: 16.36% |
| | + | ** aishell-2mix-target-3dB-SNR KCS-CER：16.69% |
| | + | ** FA test: 24h Yi Zhongtian audio：1065 times / 172800 times |
| | + | * Testing whether NLU can control FA |
| | + | ** FA PPL on n-gram LM: 405.31 |
| | + | ** positive content on n-gram LM: 95.95 |
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| | * | | * |
| 第54行： |
第65行： |
| | |Zhenghai You | | |Zhenghai You |
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| − | * | + | * Speed perturbation & Utterance augment exp；DPRNN-IRA[https://z1et6d3xtb.feishu.cn/docx/WSQvdytICo3ZHwxvVvdcRTchnIg] |
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| | * | | * |
| 第100行： |
第111行： |
| | |Pengqi Li | | |Pengqi Li |
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| − | * | + | * Learned EA-ASP with the help of Tian Hao. |
| | + | * Researched various variants of attention pooling. |
| | + | * Designed a new attention pooling with condition.[https://z1et6d3xtb.feishu.cn/docx/PgYpdmtH2oE1YexbDB8c5jW0nTh] |
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| − | * | + | * Test & Investigate |
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| | * | | * |
| 第146行： |
第159行： |
| | |Junhui Chen | | |Junhui Chen |
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| − | * | + | * Neural Scoring |
| | + | ** Exp: musan test, transformer layers test |
| | + | ** Paper writing |
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| | * | | * |
| 第198行： |
第213行： |
| | |Yang Wei | | |Yang Wei |
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| − | * | + | * AIBabel KWS |
| | + | ** Train Uyghur and Kazakh model with updated FA data |
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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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- Text enroll keyword spotting U-net
- Current AUC(U-transformer-net): 0.98
- Previous AUC(Normal transformer + keyword decoder): 0.94
- More test for next HUAWEI project (TC-ASR)
- aishell-clean-test KCS-CER: 9.34%
- aishell-2mix-target-0dB-SNR KCS-CER: 16.36%
- aishell-2mix-target-3dB-SNR KCS-CER：16.69%
- FA test: 24h Yi Zhongtian audio：1065 times / 172800 times
- Testing whether NLU can control FA
- FA PPL on n-gram LM: 405.31
- positive content on n-gram LM: 95.95
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| Zhenghai You
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- Speed perturbation & Utterance augment exp；DPRNN-IRA[2]
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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:[3]
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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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- Learned EA-ASP with the help of Tian Hao.
- Researched various variants of attention pooling.
- Designed a new attention pooling with condition.[4]
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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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- Neural Scoring
- Exp: musan test, transformer layers test
- Paper writing
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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[5]
- 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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- AIBabel KWS
- Train Uyghur and Kazakh model with updated FA data
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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[6]
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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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