Amharic-English Speech Translation in Tourism Domain

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.

Tasks

Reproductions