“2019-01-02”版本间的差异
来自cslt Wiki
Jiangxiuqi(讨论 | 贡献) |
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(5位用户的8个中间修订版本未显示) | |||
第10行: | 第10行: | ||
|Yibo Liu | |Yibo Liu | ||
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− | * | + | * Tried to reconstruct Song Iambics generation on the previous code. |
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− | * | + | * Read about GNN and try to relate it to the poem model. |
+ | * Run BERT and apply to the existing model. | ||
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第38行: | 第39行: | ||
|Jiayao Wu | |Jiayao Wu | ||
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− | * | + | * read some papers about kws and write the chapter before this weekend. |
+ | * carding the TDNN-F structure and count the lines of weights to prune and do value prune first. | ||
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− | * | + | * finish the assigned chapter of Speech book |
+ | * finish the value prune experiment | ||
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第51行: | 第54行: | ||
|Zhaodi Qi | |Zhaodi Qi | ||
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− | * | + | * read some papers about DID and other |
+ | * Run language recognition task | ||
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− | * | + | * Continue to complete the language recognition task |
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第64行: | 第68行: | ||
|Jiawei Yu | |Jiawei Yu | ||
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− | * | + | * do some Literature survey on spoken Emotion Recognition for speech book |
+ | * done for extract d-vector and phone vector for max-margin | ||
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− | * | + | * run max-margin recipe for extracted vector |
+ | * Consider how to implement the network structure | ||
+ | * finishi the speech book of spoken Emotion Recognition | ||
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第75行: | 第82行: | ||
|Yunqi Cai | |Yunqi Cai | ||
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− | * | + | *Run through the Thchs30 data, think about the research plan. |
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− | * | + | *Get to know every step of the ASR processes, and investigate the RNN LM. |
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第86行: | 第93行: | ||
|Dan He | |Dan He | ||
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− | * | + | *Compared the size of a fully connected layer after tt decomposition through experiment, at the same time compared the train loss, validation loss and test accuracy between the two case. |
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− | * | + | *Further compared the inference speed, the precision after retrain. |
+ | *Try to decompose more layers of fully connected layers. | ||
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2019年1月3日 (四) 04:50的最后版本
People | Last Week | This Week | Task Tracking (DeadLine) |
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Yibo Liu |
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Xiuqi Jiang |
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Jiayao Wu |
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Zhaodi Qi |
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Jiawei Yu |
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Yunqi Cai |
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Dan He |
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Yang Zhang |
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