“2026-01-26”版本间的差异

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（14位用户的17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 middle school hand book / English version almost completed.
 
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第17行： 第17行：
 
|Lantian Li
 
|Lantian Li
 
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* Recheck AI textbooks for senior middle school.
 
* MoE daily work (busy week)
 
* MoE daily work (busy week)
 
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第29行： 第29行：
 
|Wenqiang Du
 
|Wenqiang Du
 
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* Project work about AIbabel
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** Upgraded online model
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** New demand technology survey
 
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*
第40行： 第42行：
 
|Yang Wei
 
|Yang Wei
 
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*
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* Analyze uy/ch_child data annotation and exp result.
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* Test the av speech separation model with a dataset with more speakers.
 
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*
第51行： 第54行：
 
|Ying Shi
 
|Ying Shi
 
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*
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* Thesis
 +
* Huawei project
 
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*  
 
*  
第62行： 第66行：
 
|Yue Gu
 
|Yue Gu
 
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*
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* write my thesis
 
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*
 
*
第73行： 第77行：
 
|Lily
 
|Lily
 
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−
*
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* Organized course materials production （小初高分册）
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* Participated in reviewing the AI handbooks
 +
* Miyun 3-high school AI report
 
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*
 
*
第84行： 第90行：
 
|Pengqi Li
 
|Pengqi Li
 
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−
*
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* Experimental analysis revealed the unreliability of the insertion and deletion metrics adapted from face verification.[https://z1et6d3xtb.feishu.cn/docx/BZxUdDC1YoOSXwxQCrycW9Ymnqf]
 +
* Proposed and implemented a novel framework for assessing insertion and deletion.(still test)
 
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*
 
*
第95行： 第102行：
 
|Junming Yuan
 
|Junming Yuan
 
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−
*
+
* learn-not-to-listen MT-HuBERT
 +
** PR(PER%), LNTL-MT-HuBERT: 7.24%, Clean-HuBERT: 5.41%, WavLM: 4.84%
 +
** ASR(WER%), LNTL-MT-HuBERT: 8.43%, Clean-HuBERT: 6.42%, WavLM: 6.21%
 +
** SD(DER%), LNTL-MT-HuBERT: 4.31%, Cocktail-HuBERT: 4.07%, MT-HuBERT: 3.93%
 +
* revise ICASSP final paper
 
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*
 
*
第106行： 第117行：
 
|Yu Zhang
 
|Yu Zhang
 
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−
*
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* GPU Util: [https://z1et6d3xtb.feishu.cn/wiki/XX4NwX3tJiBDcgkMi0hcFUtInHh]
 +
* LLM
 +
** Completed the code for Swarm MMLU metric-based optimization together with @chenjunhui
 +
** Still working on modifying the Swarm topology code (for more complex swarm topology)
 
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*
 
*
第131行： 第145行：
 
|-
 
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|Jiaying Wang
 
|Jiaying Wang
 +
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* spk order separation：2-mix，3-mix training finished，testing； 4-mix are training
 +
* loudness order verification done
 +
* content order verification 1/3, will be finished these days
 
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*
 
*
 +
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*
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|-
 +
 +
 +
|-
 +
|Xiaoxue Luo
 +
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 +
* prepare 2mix speech separation results for ASR test
 +
* 2-5mix multi_head separation model for Huawei project
 +
** data: remove data that the target audio is mixed audio(input equals output, model does not learn)
 +
** loss: add MSE_loss to the original SISDR_loss to control the energy amplitude of output audio
 
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*
 
*
第143行： 第173行：
 
|Bochao Hu
 
|Bochao Hu
 
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−
*
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* read papers
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* prepare the weekly report
 
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*
 
*
第154行： 第185行：
 
|Hongcheng Zhang
 
|Hongcheng Zhang
 
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−
*
+
*made zero-shot on clotho and Audiocaps
 +
**result：ROUGE-L（0.2931，0.3998），CIDEr（0.0986，0.2312），SPIDEr（0.0800，0.1762），（clotho，Audiocaps）
 
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*
 
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第165行： 第197行：
 
|Weiman Sun
 
|Weiman Sun
 
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−
*
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*Ran a completely opposite ASR task on the same data
 +
**Consistent with last week's result
 +
*Analyze different models
 
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*
 
*

2026年2月2日 (一) 09:48的最后版本

People This Week Next Week Task Tracking (DeadLine)
Dong Wang
  • AI middle school hand book / English version almost completed.
Lantian Li
  • Recheck AI textbooks for senior middle school.
  • MoE daily work (busy week)
  • Go on the final review of my MLA book (6/10)
Wenqiang Du
  • Project work about AIbabel
    • Upgraded online model
    • New demand technology survey
Yang Wei
  • Analyze uy/ch_child data annotation and exp result.
  • Test the av speech separation model with a dataset with more speakers.
Ying Shi
  • Thesis
  • Huawei project
Yue Gu
  • write my thesis
Lily
  • Organized course materials production （小初高分册）
  • Participated in reviewing the AI handbooks
  • Miyun 3-high school AI report
Pengqi Li
  • Experimental analysis revealed the unreliability of the insertion and deletion metrics adapted from face verification.[1]
  • Proposed and implemented a novel framework for assessing insertion and deletion.(still test)
Junming Yuan
  • learn-not-to-listen MT-HuBERT
    • PR(PER%), LNTL-MT-HuBERT: 7.24%, Clean-HuBERT: 5.41%, WavLM: 4.84%
    • ASR(WER%), LNTL-MT-HuBERT: 8.43%, Clean-HuBERT: 6.42%, WavLM: 6.21%
    • SD(DER%), LNTL-MT-HuBERT: 4.31%, Cocktail-HuBERT: 4.07%, MT-HuBERT: 3.93%
  • revise ICASSP final paper
Yu Zhang
  • GPU Util: [2]
  • LLM
    • Completed the code for Swarm MMLU metric-based optimization together with @chenjunhui
    • Still working on modifying the Swarm topology code (for more complex swarm topology)
Junhui Chen
  • (caught a cold)
  • MMLU
    • difference in the ECS distribution between good nodes and bad nodes.
    • metrics loss helps select high-quality nodes and eliminate low-quality ones. [3]
Jiaying Wang
  • spk order separation：2-mix，3-mix training finished，testing； 4-mix are training
  • loudness order verification done
  • content order verification 1/3, will be finished these days
Xiaoxue Luo
  • prepare 2mix speech separation results for ASR test
  • 2-5mix multi_head separation model for Huawei project
    • data: remove data that the target audio is mixed audio(input equals output, model does not learn)
    • loss: add MSE_loss to the original SISDR_loss to control the energy amplitude of output audio
Bochao Hu
  • read papers
  • prepare the weekly report
Hongcheng Zhang
  • made zero-shot on clotho and Audiocaps
    • result：ROUGE-L（0.2931，0.3998），CIDEr（0.0986，0.2312），SPIDEr（0.0800，0.1762），（clotho，Audiocaps）
Weiman Sun
  • Ran a completely opposite ASR task on the same data
    • Consistent with last week's result
  • Analyze different models
取自“http://www.cslt.org/mediawiki/index.php?title=2026-01-26&oldid=43912”