An attentional model for speech translation without transcription

Long Duong, Antonios Anastasopoulos, David Chiang, Steven Bird, Trevor Cohn

    Research output: Chapter in Book/Report/Conference proceedingConference Paper published in Proceedings

    Abstract

    For many low-resource languages, spoken language resources are more likely to be annotated with translations than transcriptions. This bilingual speech data can be used for word-spotting, spoken document retrieval, and even for documentation of endangered languages. We experiment with the neural, attentional model applied to this data. On phoneto-word alignment and translation reranking tasks, we achieve large improvements relative to several baselines. On the more challenging speech-to-word alignment task, our model nearly matches GIZA++'s performance on gold transcriptions, but without recourse to transcriptions or to a lexicon.

    Original languageEnglish
    Title of host publication2016 Conference of the North American Chapter of the Association for Computational Linguistics
    Subtitle of host publicationHuman Language Technologies, NAACL HLT 2016 - Proceedings of the Conference
    Place of PublicationSan Diego, United States
    PublisherAssociation for Computational Linguistics (ACL)
    Pages949-959
    Number of pages11
    ISBN (Electronic)9781941643914
    Publication statusPublished - Jun 2016
    Event15th Conference of the North American Chapter of the Association for Computational Linguistics: Human Language Technologies, NAACL HLT 2016 - San Diego, United States
    Duration: 12 Jun 201617 Jun 2016

    Conference

    Conference15th Conference of the North American Chapter of the Association for Computational Linguistics: Human Language Technologies, NAACL HLT 2016
    CountryUnited States
    CitySan Diego
    Period12/06/1617/06/16

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  • Cite this

    Duong, L., Anastasopoulos, A., Chiang, D., Bird, S., & Cohn, T. (2016). An attentional model for speech translation without transcription. In 2016 Conference of the North American Chapter of the Association for Computational Linguistics: Human Language Technologies, NAACL HLT 2016 - Proceedings of the Conference (pp. 949-959). Association for Computational Linguistics (ACL).