“2025-02-10”版本间的差异
来自cslt Wiki
Yuanjunming(讨论 | 贡献) |
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| (17位用户的23个中间修订版本未显示) | |||
| 第6行: | 第6行: | ||
|Dong Wang | |Dong Wang | ||
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| − | * | + | * AI handbook high-school version v3.0 done |
| − | + | * All pictures for handbook done | |
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| 第18行: | 第18行: | ||
|Lantian Li | |Lantian Li | ||
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| − | * | + | * Final version proofreading of the high-school book (3/40) |
| + | * Preview IS2025 papers. | ||
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| 第29行: | 第30行: | ||
|Ying Shi | |Ying Shi | ||
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| − | * | + | * https://z1et6d3xtb.feishu.cn/docx/Wg3ldbCKeoKhBzxZ2lccTO8ZnTf?from=from_copylink |
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| 第41行: | 第42行: | ||
|Zhenghai You | |Zhenghai You | ||
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| − | * | + | * Revise the Is2025 paper to the second edition |
| + | * Reading some papers on SE/SS/TSE refiner | ||
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| 第51行: | 第53行: | ||
|Junming Yuan | |Junming Yuan | ||
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| − | * | + | * High-school PPT and Jiaoan(4) |
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| 第62行: | 第64行: | ||
|Xiaolou Li | |Xiaolou Li | ||
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| − | * | + | * Write CNVSRC2024 paper |
| + | * Config Gongan Server and copy data to it | ||
| + | * pre-process cvs3 data | ||
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| 第73行: | 第77行: | ||
|Zehua Liu | |Zehua Liu | ||
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| − | * | + | *Writing CNVSRC-2024 paper |
| + | *Writing VSR-LLM paper and Doing Experiment | ||
| + | *AlignVSR Current Result on LRS3 (WER:33.9%) < SyncVSR(WER:33.3%)(Maybe need change hyper-parameter) | ||
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| 第84行: | 第90行: | ||
|Pengqi Li | |Pengqi Li | ||
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| − | * | + | * High-school PPT and Jiaoan(5) |
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| 第95行: | 第101行: | ||
|Wan Lin | |Wan Lin | ||
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| − | * | + | * Revised NS paper for IS2025 [https://z1et6d3xtb.feishu.cn/docx/PqtDdWPSwomSDexW2oUc2M4qnrc?from=from_copylink] (still lack of experimental results) |
| + | * Train multi-scenario model (need parameters adjusting, still in training) | ||
| + | * Try other revised-BCE loss(failed) | ||
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| 第106行: | 第114行: | ||
|Tianhao Wang | |Tianhao Wang | ||
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| − | * | + | * reproducing two baselines: Universal sound separation and MixIT |
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| 第117行: | 第125行: | ||
|Xiaoxue Luo | |Xiaoxue Luo | ||
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| − | * | + | * Check the pictures in AI high school handbook,completed the first chapter(1/4) |
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| 第128行: | 第136行: | ||
|Zhenyu Zhou | |Zhenyu Zhou | ||
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| − | * | + | * write graduation paper |
| + | * conditional chain experiment & paper draft with jiaying | ||
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| 第152行: | 第161行: | ||
|Jiaying Wang | |Jiaying Wang | ||
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| − | * | + | * is25 paper: abstract, intro, related work, method, dataset parts have been finished[https://z1et6d3xtb.feishu.cn/docx/TUHldiaoQoYBqux7JEhcaCXenzh] |
| + | * experiment: baseline with pit and cc: training and test all finished | ||
| + | * model which sort by ctc: coding, finished in these days | ||
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| 第163行: | 第174行: | ||
|Yu Zhang | |Yu Zhang | ||
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| − | * | + | * refine prompt |
| + | * add backtesting report to debate report | ||
| + | * trying stronger model (DeepSeek R1 70B) | ||
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| − | * | + | * introduce more trading groups that are mutually opposed. |
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| 第174行: | 第187行: | ||
|Wenqiang Du | |Wenqiang Du | ||
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| − | * | + | * AI primary handbook PPT (16/35) |
| + | * Check AI primary handbook | ||
| + | * Check AI middle handbook | ||
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| 第185行: | 第200行: | ||
|Yang Wei | |Yang Wei | ||
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| − | * | + | * Train text enroll kws model with short audio data. (recall mandarin: 80%, yue: 88%) |
| + | * Train model with larger model; finetune with fyt recording data. (In progress) | ||
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| 第195行: | 第211行: | ||
|Turi | |Turi | ||
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| − | * | + | * Text data collection |
| + | * Adding Language Model to ASR (not successful yet) | ||
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| 第203行: | 第220行: | ||
|Yue Gu | |Yue Gu | ||
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| − | * | + | * almost finish phone-level gaussian model training |
| + | * according to the badcase analysis,I‘m designing a new framework for fine-grained speaker adaptation | ||
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| 第212行: | 第230行: | ||
|Qi Qu | |Qi Qu | ||
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| − | * | + | * Porting Text-enroll KWS models (delivery 2025-01-08) to mr536 NPU. |
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2025年2月11日 (二) 03:13的最后版本
| People | This Week | Next Week | Task Tracking (DeadLine) |
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| Dong Wang |
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| Lantian Li |
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| Ying Shi |
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| Zhenghai You |
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| Junming Yuan |
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| Xiaolou Li |
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| Zehua Liu |
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| Pengqi Li |
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| Wan Lin |
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| Tianhao Wang |
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| Xiaoxue Luo |
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| Zhenyu Zhou |
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| Junhui Chen |
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| Jiaying Wang |
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| Yu Zhang |
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| Wenqiang Du |
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| Yang Wei |
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| Turi |
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| Yue Gu |
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| Qi Qu |
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