CRF를 이용한 운율경계추정 성능개선
KCI
- Title
- CRF를 이용한 운율경계추정 성능개선
- Authors
- 김병창; 김승원; 이근배
- Date Issued
- 2006-03
- Publisher
- 대한음성학회
- Abstract
- Improvements on Phrase Breaks Prediction Using CRF (Conditional Random Fields)Byeongchang Kim, Seungwon Kim, Gary Geunbae LeeIn this paper, we present a phrase break prediction method using CRF(Conditional Random Fields), which has good performance at classification problems. The phrase break prediction problem was mapped into a classification problem in our research. We trained the CRF using the various linguistic features which was extracted from POS(Part Of Speech) tag, lexicon, length of word, and location of word in the sentences. Combined linguistic features were used in the experiments, and we could collect some linguistic features which generate good performance in the phrase break prediction. From the results of experiments, we can see that the proposed method shows improved performance on previous methods. Additionally, because the linguistic features are independent of each other in our research, the proposed method has higher flexibility than other methods.
- URI
- https://oasis.postech.ac.kr/handle/2014.oak/31558
- ISSN
- 1226-1173
- Article Type
- Article
- Citation
- 말소리, vol. 57, page. 139 - 152, 2006-03
- Files in This Item:
- There are no files associated with this item.
Items in DSpace are protected by copyright, with all rights reserved, unless otherwise indicated.