Transfer-based statistical translation of Taiwanese sign language using PCFG

Chung Hsien Wu, Hung Yu Su, Yu Hsien Chiu, Chia Hung Lin

研究成果: Article

12 引文 斯高帕斯(Scopus)


This article presents a transfer-based statistical model for Chinese to Taiwanese sign-language (TSL) translation. Two sets of probabilistic context-free grammars (PCFGs) are derived from a Chinese Treebank and a bilingual parallel corpus. In this approach, a three-stage translation model is proposed. First, the input Chinese sentence is parsed into possible phrase structure trees (PSTs) based on the Chinese PCFGs. Second, the Chinese PSTs are then transferred into TSL PSTs according to the transfer probabilities between the context-free grammar (CFG) rules of Chinese and TSL derived from the bilingual parallel corpus. Finally, the TSL PSTs are used to generate the possible translation results. The Viterbi algorithm is adopted to obtain the best translation result via the three-stage translation. For evaluation, three objective evaluation metrics including AER, Top-N, and BLUE and one subjective evaluation metric using MOS were used. Experimental results show that the proposed approach outperforms the IBM Model 3 in the task of Chinese to sign-language translation.

期刊ACM Transactions on Asian Language Information Processing
出版狀態Published - 2007 四月 1

All Science Journal Classification (ASJC) codes

  • Computer Science(all)

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