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Machine Translation of Speech (SLP-SSMT)

Prosodic Annotation Enriched Statistical Machine Translation


More and more linguistic information has been employed to improve the performance of machine translation, such as part of speech, syntactic structures, discourse contexts, and so on. However, conventional approaches typically ignore the key information beyond the text such as prosody. In this paper, we exploit and employ three prosodic features: pronunciation (phonetic alphabet and tone), prosodic boundaries and emphasis.

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Authors:
Peidong Guo, Heyan Huang, Ping Jian, Yuhang Guo
Submitted On:
15 October 2016 - 12:10pm
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Prosodic Annotation Enriched Statistical Machine Translation(161014).pdf

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[1] Peidong Guo, Heyan Huang, Ping Jian, Yuhang Guo, "Prosodic Annotation Enriched Statistical Machine Translation", IEEE SigPort, 2016. [Online]. Available: http://sigport.org/1250. Accessed: Dec. 15, 2017.
@article{1250-16,
url = {http://sigport.org/1250},
author = {Peidong Guo; Heyan Huang; Ping Jian; Yuhang Guo },
publisher = {IEEE SigPort},
title = {Prosodic Annotation Enriched Statistical Machine Translation},
year = {2016} }
TY - EJOUR
T1 - Prosodic Annotation Enriched Statistical Machine Translation
AU - Peidong Guo; Heyan Huang; Ping Jian; Yuhang Guo
PY - 2016
PB - IEEE SigPort
UR - http://sigport.org/1250
ER -
Peidong Guo, Heyan Huang, Ping Jian, Yuhang Guo. (2016). Prosodic Annotation Enriched Statistical Machine Translation. IEEE SigPort. http://sigport.org/1250
Peidong Guo, Heyan Huang, Ping Jian, Yuhang Guo, 2016. Prosodic Annotation Enriched Statistical Machine Translation. Available at: http://sigport.org/1250.
Peidong Guo, Heyan Huang, Ping Jian, Yuhang Guo. (2016). "Prosodic Annotation Enriched Statistical Machine Translation." Web.
1. Peidong Guo, Heyan Huang, Ping Jian, Yuhang Guo. Prosodic Annotation Enriched Statistical Machine Translation [Internet]. IEEE SigPort; 2016. Available from : http://sigport.org/1250