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第161行： |
| | |Hongcheng Zhang | | |Hongcheng Zhang |
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| − | * | + | *Complete the training of short audio descriptions for AudioSet-SL in WavCaps： |
| | + | *METEOR: 0.3373 ROUGE-L: 0.3121 BLEU-4 : 0.0769 CIDEr : 0.6207 |
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| People |
This Week |
Next Week |
Task Tracking (DeadLine)
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| Dong Wang
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- Recheck AI textbooks for primary and middle schools.
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| Lantian Li
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| Wenqiang Du
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- Statistics the accounts for three companies, our laboratory and AIGE.
- Check AI textbooks
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| Yang Wei
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| Ying Shi
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- Thesis
- Huawei multi-talker ASR project(Mandarin 2-mix test with FunASR-Nano-800M)
- ground-truth WER 3.89%
- separated WER 12.11%
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| Yue Gu
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- write my Phd thesis
- the seminar
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| Lily
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- Participated in reviewing the AI handbooks (primary/middle/high school)
- Compiled course materials for the AI Handbook (Senior Edition)
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| Pengqi Li
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| Junming Yuan
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- Aug-MT-HuBERT(failed)
- Continued pre-training for 600K steps. there is still no improvement observed on clean-speech tasks.
- Aug-MT-HuBERT has more substitution errors in clean ASR adaptation.
- Incorporate a "learn-not-to-listen" mechanism into MT-HuBERT and retrain the backbone. (in progress)
- At 425K steps, PR(PER%): 8.18%, ASR(WER%): 9.32%, SD(DER%): 5.05%
- prepare the slides of the seminar
- middle school AI textbook checking(picture, table)
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| Yu Zhang
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| Junhui Chen
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| Jiaying Wang
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| Bochao Hu
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| Hongcheng Zhang
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- Complete the training of short audio descriptions for AudioSet-SL in WavCaps：
*METEOR: 0.3373 ROUGE-L: 0.3121 BLEU-4 : 0.0769 CIDEr : 0.6207
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| Weiman Sun
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- Label audioset vedio dataset
- Analyze the representation of MT-LLM inference and review relevant literature
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