Hierarchical Phrase-Based MT for Phonetic Representation-Based Speech Translation

Zeeshan Ahmed, Jie Jiang, Julie Carson-Berndsen, Peter Cahill, Andy Way


Abstract
The paper presents a novel technique for speech translation using hierarchical phrased-based statistical machine translation (HPB-SMT). The system is based on translation of speech from phone sequences as opposed to conventional approach of speech translation from word sequences. The technique facilitates speech translation by allowing a machine translation (MT) system to access to phonetic information. This enables the MT system to act as both a word recognition and a translation component. This results in better performance than conventional speech translation approaches by recovering from recognition error with help of a source language model, translation model and target language model. For this purpose, the MT translation models are adopted to work on source language phones using a grapheme-to-phoneme component. The source-side phonetic confusions are handled using a confusion network. The result on IWLST'10 English- Chinese translation task shows a significant improvement in translation quality. In this paper, results for HPB-SMT are compared with previously published results of phrase-based statistical machine translation (PB-SMT) system (Baseline). The HPB-SMT system outperforms PB-SMT in this regard.
Anthology ID:
2012.amta-papers.1
Volume:
Proceedings of the 10th Conference of the Association for Machine Translation in the Americas: Research Papers
Month:
October 28-November 1
Year:
2012
Address:
San Diego, California, USA
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AMTA
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Publisher:
Association for Machine Translation in the Americas
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URL:
https://aclanthology.org/2012.amta-papers.1
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Cite (ACL):
Zeeshan Ahmed, Jie Jiang, Julie Carson-Berndsen, Peter Cahill, and Andy Way. 2012. Hierarchical Phrase-Based MT for Phonetic Representation-Based Speech Translation. In Proceedings of the 10th Conference of the Association for Machine Translation in the Americas: Research Papers, San Diego, California, USA. Association for Machine Translation in the Americas.
Cite (Informal):
Hierarchical Phrase-Based MT for Phonetic Representation-Based Speech Translation (Ahmed et al., AMTA 2012)
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PDF:
https://aclanthology.org/2012.amta-papers.1.pdf