Enhancing ASR by MT using Semantic Information from HindiWordNet

Aniruddha Tammewar, Karan Singla, Srinivas Bangalore, Michael Carl

    Publikation: KonferencebidragPosterForskningpeer review

    Resumé

    In a conventional CAT (Computer Assisted Translation) system a human translator post-edits an automatically generated target language text using the keyboard. In this paper we extend a CAT system with speech input by which the translator speaks the translation, a process refered to as sight translation. We report several experiments to improve the performance of an automatic speech recognition system, taking advantage of machine translation output and information fromWordNet. Overall we outperform a baseline system which has no semantic information by an increased 1.6% word accuracy for the English to Hindi translation.
    OriginalsprogEngelsk
    Publikationsdato2013
    StatusUdgivet - 2013
    Begivenhed10th International Conference on Natural Language Processing - Centre for Development of Advanced Computing, Noida, Indien
    Varighed: 18 dec. 201320 dec. 2013
    Konferencens nummer: 10
    http://ltrc.iiit.ac.in/icon/2013/index.php

    Konference

    Konference10th International Conference on Natural Language Processing
    Nummer10
    LokationCentre for Development of Advanced Computing
    LandIndien
    ByNoida
    Periode18/12/201320/12/2013
    Internetadresse

    Bibliografisk note

    CBS Bibliotek har ikke adgang til materialet

    Citer dette

    Tammewar, A., Singla, K., Bangalore, S., & Carl, M. (2013). Enhancing ASR by MT using Semantic Information from HindiWordNet. Poster session præsenteret på 10th International Conference on Natural Language Processing, Noida, Indien.
    Tammewar, Aniruddha ; Singla, Karan ; Bangalore, Srinivas ; Carl, Michael. / Enhancing ASR by MT using Semantic Information from HindiWordNet. Poster session præsenteret på 10th International Conference on Natural Language Processing, Noida, Indien.
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    title = "Enhancing ASR by MT using Semantic Information from HindiWordNet",
    abstract = "In a conventional CAT (Computer Assisted Translation) system a human translator post-edits an automatically generated target language text using the keyboard. In this paper we extend a CAT system with speech input by which the translator speaks the translation, a process refered to as sight translation. We report several experiments to improve the performance of an automatic speech recognition system, taking advantage of machine translation output and information fromWordNet. Overall we outperform a baseline system which has no semantic information by an increased 1.6{\%} word accuracy for the English to Hindi translation.",
    author = "Aniruddha Tammewar and Karan Singla and Srinivas Bangalore and Michael Carl",
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    Tammewar, A, Singla, K, Bangalore, S & Carl, M 2013, 'Enhancing ASR by MT using Semantic Information from HindiWordNet' 10th International Conference on Natural Language Processing, Noida, Indien, 18/12/2013 - 20/12/2013, .

    Enhancing ASR by MT using Semantic Information from HindiWordNet. / Tammewar, Aniruddha ; Singla, Karan ; Bangalore, Srinivas ; Carl, Michael.

    2013. Poster session præsenteret på 10th International Conference on Natural Language Processing, Noida, Indien.

    Publikation: KonferencebidragPosterForskningpeer review

    TY - CONF

    T1 - Enhancing ASR by MT using Semantic Information from HindiWordNet

    AU - Tammewar, Aniruddha

    AU - Singla, Karan

    AU - Bangalore, Srinivas

    AU - Carl, Michael

    N1 - CBS Library does not have access to the material

    PY - 2013

    Y1 - 2013

    N2 - In a conventional CAT (Computer Assisted Translation) system a human translator post-edits an automatically generated target language text using the keyboard. In this paper we extend a CAT system with speech input by which the translator speaks the translation, a process refered to as sight translation. We report several experiments to improve the performance of an automatic speech recognition system, taking advantage of machine translation output and information fromWordNet. Overall we outperform a baseline system which has no semantic information by an increased 1.6% word accuracy for the English to Hindi translation.

    AB - In a conventional CAT (Computer Assisted Translation) system a human translator post-edits an automatically generated target language text using the keyboard. In this paper we extend a CAT system with speech input by which the translator speaks the translation, a process refered to as sight translation. We report several experiments to improve the performance of an automatic speech recognition system, taking advantage of machine translation output and information fromWordNet. Overall we outperform a baseline system which has no semantic information by an increased 1.6% word accuracy for the English to Hindi translation.

    M3 - Poster

    ER -

    Tammewar A, Singla K, Bangalore S, Carl M. Enhancing ASR by MT using Semantic Information from HindiWordNet. 2013. Poster session præsenteret på 10th International Conference on Natural Language Processing, Noida, Indien.