@inproceedings{ahmed-etal-2012-hierarchical,
    title = "Hierarchical Phrase-Based {MT} for Phonetic Representation-Based Speech Translation",
    author = "Ahmed, Zeeshan  and
      Jiang, Jie  and
      Carson-Berndsen, Julie  and
      Cahill, Peter  and
      Way, Andy",
    booktitle = "Proceedings of the 10th Conference of the Association for Machine Translation in the Americas: Research Papers",
    month = oct # " 28-" # nov # " 1",
    year = "2012",
    address = "San Diego, California, USA",
    publisher = "Association for Machine Translation in the Americas",
    url = "https://preview.aclanthology.org/ingest_wac_2008/2012.amta-papers.1/",
    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."
}