| dc.contributor.author | Nabende, Peter | |
| dc.date.accessioned | 2012-02-03T15:49:05Z | |
| dc.date.available | 2012-02-03T15:49:05Z | |
| dc.date.issued | 2009-08-07 | |
| dc.identifier.citation | Nabende, P. (2009). Transliteration system using pair HMM with weighted FSTs. In Proceedings of the 2009 named entities workshop: shared task on machine transliteration, ACL-IJCNLP, Singapore. Pages 100-103. | en_US |
| dc.identifier.isbn | 978-1-932432-57-2 | |
| dc.identifier.isbn | 1-932432-57-4 | |
| dc.identifier.uri | http://hdl.handle.net/10570/380 | |
| dc.description | This paper presents a transliteration system based on pair Hidden Markov Model (pair HMM) training and weighted Finite State Transducer (WFST)techniques. | en_US |
| dc.description.abstract | This paper presents a transliteration system based on pair Hidden Markov Model (pair HMM) training and weighted Finite State Transducer (WFST)techniques. Parameters used by WFSTs for transliteration generation are learned from a pair HMM. Parameters from pair HMM training on English-Russian data sets are found to give better transliteration quality than parameters trained for WFSTs for corresponding structures. Training a pair HMM on English vowel bigrams and standard bigrams for Cyrillic Romanization and using a few transformation rules on generated Russian transliterations to test for context improves the system's transliteration quality. | en_US |
| dc.description.sponsorship | Nuffic | en_US |
| dc.language.iso | en | en_US |
| dc.publisher | World Scientific Publishing Co Pte Ltd | en_US |
| dc.subject | Machine transliteration | en_US |
| dc.subject | Pair hidden markov model | en_US |
| dc.subject | Weighted finite state transducers | en_US |
| dc.title | Transliteration system using pair HMM with weighted FSTs | en_US |
| dc.type | Conference paper | en_US |
