“Hulan-2013-11-30”版本间的差异
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==ASR Kernel development== | ==ASR Kernel development== | ||
| − | [[http://cslt.riit.tsinghua.edu.cn/mediawiki/index.php/2013-11- | + | [[http://cslt.riit.tsinghua.edu.cn/mediawiki/index.php/2013-11-29 ASR group weekly report]] |
==TTS== | ==TTS== | ||
| − | * 5000 utterance training done. | + | * This week |
| − | * 500 utterance TN recording done. Quality control is not very good. Resulting synthesis is not satisfied. | + | :* 5000 utterance training done. |
| − | * 41 WD utterance recording. Quality control fine. Adaptation done. Sounds OK. | + | :* 500 utterance TN recording done. Quality control is not very good. Resulting synthesis is not satisfied. |
| − | * Buzzy sound was investigated.The main source is the source model (excitation). STRAIGHT sounds better. | + | :* 41 WD utterance recording. Quality control fine. Adaptation done. Sounds OK. |
| − | * Developing CGI service. | + | :* Buzzy sound was investigated.The main source is the source model (excitation). STRAIGHT sounds better. |
| + | |||
| + | * Next week | ||
| + | :* Developing CGI service. | ||
| + | :* Prepare to 2000 utt female record. | ||
=Dialog system= | =Dialog system= | ||
| + | |||
| + | ==Statistical approach== | ||
* HowNET information extracted. Coverage is limited. 50k words. | * HowNET information extracted. Coverage is limited. 50k words. | ||
2013年11月29日 (五) 04:00的最后版本
目录
ASR
ASR Kernel development
TTS
- This week
- 5000 utterance training done.
- 500 utterance TN recording done. Quality control is not very good. Resulting synthesis is not satisfied.
- 41 WD utterance recording. Quality control fine. Adaptation done. Sounds OK.
- Buzzy sound was investigated.The main source is the source model (excitation). STRAIGHT sounds better.
- Next week
- Developing CGI service.
- Prepare to 2000 utt female record.
Dialog system
Statistical approach
- HowNET information extracted. Coverage is limited. 50k words.
- Custom task error analysis
There are totally 2000 errors. Investigated into 600 errors.
- NULL query, 1.4%
- English upper/lower mismatch. 1.6%
- Traditional/Simple Chinese mismatch. 2.2%
- High frequency of sub-important words, like taxing. 1.3%
- Database labeling error (matched query is better than the labeled correct query). 21.8%
- Stand query or query involve many unimportant words, leading to less TF/IDF. STOP words still impact. 10.7%
- TF/IDF incorrectly weighted the matched terms. 3.9%
- Synonym can not match. 36.5%
- Category words can not match. 13.5%
- Answer label incorrect. Semantic relationship missing. 6.8%
- Word segmentation hide keywords. 4%
- Vague query. None discriminative words after stop words purging. 1.6%
Template matching
- Work on disambiguousness
- Completed the prototype design for the QA logic
- Develop an assistant tool for source code generation
