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.- Anthology ID:
- W17-4608
- Volume:
- Proceedings of the Workshop on Speech-Centric Natural Language Processing
- Month:
- September
- Year:
- 2017
- Address:
- Copenhagen, Denmark
- Editors:
- Nicholas Ruiz, Srinivas Bangalore
- Venue:
- WS
- SIG:
- Publisher:
- Association for Computational Linguistics
- Note:
- Pages:
- 59–66
- Language:
- URL:
- https://aclanthology.org/W17-4608
- DOI:
- 10.18653/v1/W17-4608
- Cite (ACL):
- Michael Melese, Laurent Besacier, and Million Meshesha. 2017. Amharic-English Speech Translation in Tourism Domain. In Proceedings of the Workshop on Speech-Centric Natural Language Processing, pages 59–66, Copenhagen, Denmark. Association for Computational Linguistics.
- Cite (Informal):
- Amharic-English Speech Translation in Tourism Domain (Melese et al., 2017)
- PDF:
- https://preview.aclanthology.org/ml4al-ingestion/W17-4608.pdf