@InProceedings{melese-besacier-meshesha:2017:Speech-Centric,
  author    = {Melese, Michael  and  Besacier, Laurent  and  Meshesha, Million},
  title     = {Amharic-English Speech Translation in Tourism Domain},
  booktitle = {Proceedings of the Workshop on Speech-Centric Natural Language Processing},
  month     = {September},
  year      = {2017},
  address   = {Copenhagen, Denmark},
  publisher = {Association for Computational Linguistics},
  pages     = {59--66},
  abstract  = {This paper describes speech translation from Amharic-to-English, particularly
	Automatic Speech Recognition (ASR) with post-editing feature and
	Amharic-English Statistical Machine Translation (SMT). ASR experiment is
	conducted using morpheme language model (LM) and phoneme acoustic model(AM).
	Likewise,SMT conducted using word and morpheme as unit. 
	Morpheme based translation shows a 6.29 BLEU score at a 76.4% of recognition
	accuracy while word based translation shows a 12.83 BLEU score using 77.4% word
	recognition accuracy. Further, after post-edit on Amharic ASR using corpus
	based n-gram, the word recognition accuracy increased by 1.42%. Since post-edit
	approach reduces error propagation, the word based translation accuracy
	improved by 0.25 (1.95%) BLEU score. We are now working towards further
	improving propagated errors through different algorithms at each unit of speech
	translation cascading component.},
  url       = {http://www.aclweb.org/anthology/W17-4608}
}