Transfer-based statistical translation of Taiwanese sign language using PCFG

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

Research output: Contribution to journalArticlepeer-review

12 Citations (Scopus)

Abstract

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.

Original languageEnglish
Article number1227851
JournalACM Transactions on Asian Language Information Processing
Volume6
Issue number1
DOIs
Publication statusPublished - 2007 Apr 1

All Science Journal Classification (ASJC) codes

  • Computer Science(all)

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