@inproceedings{saha-bandyopadhyay-2005-semantics,
title = "A Semantics-based {E}nglish-{B}engali {EBMT} System for Translating News Headlines",
author = "Saha, Diganta and
Bandyopadhyay, Sivaji",
booktitle = "Workshop on example-based machine translation",
month = sep # " 13-15",
year = "2005",
address = "Phuket, Thailand",
url = "https://aclanthology.org/2005.mtsummit-ebmt.16",
pages = "125--133",
abstract = "The paper reports an Example based Machine Translation System for translating News Headlines from English to Bengali. The input headline is initially searched in the Direct Example Base. If it cannot be found, the input headline is tagged and the tagged headline is searched in the Generalized Tagged Example Base. If a match is obtained, the tagged headline in Bengali is retrieved from the example base, the output Bengali headline is generated after retrieving the Bengali equivalents of the English words from appropriate dictionaries and then applying relevant synthesis rules for generating the Bengali surface level words. If some named entities and acronyms are not present in the dictionary, transliteration scheme is applied for obtaining the Bengali equivalent. If a match is not found, the tagged input headline is analysed to identify the constituent phrase(s). The target translation is generated using English-Bengali phrasal example base, appropriate dictionaries and a set of heuristics for Bengali phrase reordering. If the headline still cannot be translated using example base strategy, a heuristic translation strategy will be applied. Any new input tagged headline along with its translation by the user will be inserted in the tagged Example base after generalization.",
}
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%0 Conference Proceedings
%T A Semantics-based English-Bengali EBMT System for Translating News Headlines
%A Saha, Diganta
%A Bandyopadhyay, Sivaji
%S Workshop on example-based machine translation
%D 2005
%8 sep 13 15
%C Phuket, Thailand
%F saha-bandyopadhyay-2005-semantics
%X The paper reports an Example based Machine Translation System for translating News Headlines from English to Bengali. The input headline is initially searched in the Direct Example Base. If it cannot be found, the input headline is tagged and the tagged headline is searched in the Generalized Tagged Example Base. If a match is obtained, the tagged headline in Bengali is retrieved from the example base, the output Bengali headline is generated after retrieving the Bengali equivalents of the English words from appropriate dictionaries and then applying relevant synthesis rules for generating the Bengali surface level words. If some named entities and acronyms are not present in the dictionary, transliteration scheme is applied for obtaining the Bengali equivalent. If a match is not found, the tagged input headline is analysed to identify the constituent phrase(s). The target translation is generated using English-Bengali phrasal example base, appropriate dictionaries and a set of heuristics for Bengali phrase reordering. If the headline still cannot be translated using example base strategy, a heuristic translation strategy will be applied. Any new input tagged headline along with its translation by the user will be inserted in the tagged Example base after generalization.
%U https://aclanthology.org/2005.mtsummit-ebmt.16
%P 125-133
Markdown (Informal)
[A Semantics-based English-Bengali EBMT System for Translating News Headlines](https://aclanthology.org/2005.mtsummit-ebmt.16) (Saha & Bandyopadhyay, MTSummit 2005)
ACL