Enhancing ASR by MT using Semantic Information from HindiWordNet

Aniruddha Tammewar, Karan Singla, Srinivas Bangalore, Michael Carl

    Research output: Contribution to conferencePosterResearchpeer-review

    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.
    Original languageEnglish
    Publication date2013
    Publication statusPublished - 2013
    Event10th International Conference on Natural Language Processing - Centre for Development of Advanced Computing, Noida, India
    Duration: 18 Dec 201320 Dec 2013
    Conference number: 10
    http://ltrc.iiit.ac.in/icon/2013/index.php

    Conference

    Conference10th International Conference on Natural Language Processing
    Number10
    LocationCentre for Development of Advanced Computing
    CountryIndia
    CityNoida
    Period18/12/201320/12/2013
    Internet address

    Bibliographical note

    CBS Library does not have access to the material

    Cite this

    Tammewar, A., Singla, K., Bangalore, S., & Carl, M. (2013). Enhancing ASR by MT using Semantic Information from HindiWordNet. Poster session presented at 10th International Conference on Natural Language Processing, Noida, India.
    Tammewar, Aniruddha ; Singla, Karan ; Bangalore, Srinivas ; Carl, Michael. / Enhancing ASR by MT using Semantic Information from HindiWordNet. Poster session presented at 10th International Conference on Natural Language Processing, Noida, India.
    @conference{1592faa9db6d460390203c8cf3e66118,
    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",
    note = "CBS Library does not have access to the material; null ; Conference date: 18-12-2013 Through 20-12-2013",
    year = "2013",
    language = "English",
    url = "http://ltrc.iiit.ac.in/icon/2013/index.php",

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    Tammewar, A, Singla, K, Bangalore, S & Carl, M 2013, 'Enhancing ASR by MT using Semantic Information from HindiWordNet', Noida, India, 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 presented at 10th International Conference on Natural Language Processing, Noida, India.

    Research output: Contribution to conferencePosterResearchpeer-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 presented at 10th International Conference on Natural Language Processing, Noida, India.