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| 第31行： |
第31行： |
| | |Ying Shi | | |Ying Shi |
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| − | * | + | * Finish SPL paper version1 |
| | + | * Wake Up model test with real speech |
| | + | * Chinese Phrase-Guided ASR model test with real speech [https://z1et6d3xtb.feishu.cn/wiki/YU81wRCdTijmUxkQWtTcApJTnXf?from=from_copylink group work] |
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| People |
This Week |
Next Week |
Task Tracking (DeadLine)
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| Dong Wang
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- Interspeech review
- AI primary education design
- <Illustraitver AI> slides refinement
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| Lantian Li
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| Ying Shi
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- Finish SPL paper version1
- Wake Up model test with real speech
- Chinese Phrase-Guided ASR model test with real speech group work
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| Zhenghai You
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- Retrain a SpEx+ model more suitable for online
- Reflect on cohort and reorganized document
- paper reading
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| Junming Yuan
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- prepare materials of live broadcast
- paper reading
- got sick
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| Chen Chen
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| Xiaolou Li
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| Zehua Liu
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- auxiliary loss exp[1]
- crop_size exp(still training)
- read papper
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- reproduce other architecture
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| Pengqi Li
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- speech XAI review v1[2]
- polished poster
- live broadcast
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| Wan Lin
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- Explore multi-speaker training in NS (how to get batter result in all condition)
- use wespeaker toolkit
- effect of time of training sample
- inherit hard speaker sample
- add channel-time attention in ResNet to get enroll-aware test feature
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| Tianhao Wang
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- EA-ASP exps
- aligned toolkit (wespeaker To sunine), failed. we will align to wespeaker
- aligned training data (weak overlap To strong overlap)
- concat and weak_overlap worse, overlap and mix better compared to previous
- NS arch. has advantages under mix, but non under other tests compared to EA-ASP
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- read paper
- reproduce SpEx+ in TSV
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| Zhenyu Zhou
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| Junhui Chen
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- Neural Scoring result [3]
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| Jiaying Wang
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- re-organized document 0025[4]
- SS_based: Conv-Tasnet with one fixed cohort(still training)[5]
- paper reading
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| Yu Zhang
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- SAC model training and backtesting [6]
- financial quantile work pipeline finish
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- add more data to pipeline (more benchmark and more training testing data range)
- append financial-pipeline design and implement detail doc
- AutoML for stock return regression
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| Wenqiang Du
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- Efficient-B6 pretrain model training
- hard negative training
- FA data is being collected
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| Yang Wei
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- Children mispronunciation detection
- Analyze and check the baseline model
- Huilan
- ASR service bug fix and update
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| Lily
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- Paper reading [7]
- Assisted to prepare AI graph course materials and PPTs
- Prepare for AI radiance live broadcast
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| Turi
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- Data collection App[8]
- Tested the app and Fixed some bugs
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| Qi Qu
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- Server-side KWS:
- Tested with EfficientNetB{2,4,6,8}
- Service to be implemented with EfficientNetB6 (preview)
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| Yue Gu
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- complete the most experiments of contextual ASR
- complete the pseudocodes of group stage and bias-phrase decoding lattice
- read one paper
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