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| 第17行： |
第17行： |
| | *integrated tone_model to attention_model for insteading manul rule,but the effect wasn't good | | *integrated tone_model to attention_model for insteading manul rule,but the effect wasn't good |
| | *replacing all_pz rule with half_pz | | *replacing all_pz rule with half_pz |
| − | *token a classical Chinese as input,generated poem | + | *token a classical Chinese as input,generated poem [http://cslt.riit.tsinghua.edu.cn/mediawiki/images/3/33/Story_input.pdf] |
| | || | | || |
| | *improve poem model | | *improve poem model |
| Date |
People |
Last Week |
This Week
|
| 2016/12/26
|
Yang Feng |
- s2smn: read six papers to fix the details of our model;
- wrote the proposal of lexical memory and discussed the details with Teach Wang;
- finished coding of only adding attention to the decoder and under debugging;
- refine Moses manual [manual] ;
- prepare the dictionary for the memory loading;
- Huilan: documentation
|
|
| Jiyuan Zhang |
- integrated tone_model to attention_model for insteading manul rule,but the effect wasn't good
- replacing all_pz rule with half_pz
- token a classical Chinese as input,generated poem [1]
|
|
| Andi Zhang |
- coded to output encoder outputs and correspoding source & target sentences(ids in dictionaries)
- coded a script for bleu scoring, which tests the five checkpoints auto created by training process and save the one with best performance
|
|
| Shiyue Zhang |
- tried to add true action info when training gate, which got better results than no true actions, but still not very good.
- tried different scale vectors, and found setting >=-5000 is good
- tried to change cos to only inner product, and inner product is better than cos.
- [report]
- read 3 papers [[2]] [[3]] [[4]]
- trying the joint training, which got a problem of optimization.
|
- try the joint training
- read more papers and write a summary
|
| Guli |
- finished the first draft of the survey
- voice tagging
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- morpheme-based nmt
- improve nmt with monolingual data
|
| Peilun Xiao |
- learned tf-idf algorithm
- coded tf-idf alogrithm in python,but found it not worked well
- tried to use small dataset to test the program
|
- use sklearn tfidf to test the dataset
|
