TY - JOUR
T1 - Transfer-based statistical translation of Taiwanese sign language using PCFG
AU - Wu, Chung Hsien
AU - Su, Hung Yu
AU - Chiu, Yu Hsien
AU - Lin, Chia Hung
PY - 2007/4/1
Y1 - 2007/4/1
N2 - 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.
AB - 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.
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U2 - 10.1145/1227850.1227851
DO - 10.1145/1227850.1227851
M3 - Article
AN - SCOPUS:34247182112
VL - 6
JO - ACM Transactions on Asian Language Information Processing
JF - ACM Transactions on Asian Language Information Processing
SN - 1530-0226
IS - 1
M1 - 1227851
ER -