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Language Models for Machine Translation: Original vs. Translated Texts

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Computational Linguistics

MIT Press - Journals

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      A maximum likelihood approach to continuous speech recognition.

      Speech recognition is formulated as a problem of maximum likelihood decoding. This formulation requires statistical models of the speech production process. In this paper, we describe a number of statistical models for use in speech recognition. We give special attention to determining the parameters for such models from sparse data. We also describe two decoding methods, one appropriate for constrained artificial languages and one appropriate for more realistic decoding tasks. To illustrate the usefulness of the methods described, we review a number of decoding results that have been obtained with them.
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        Moses

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          Statistical phrase-based translation

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            Author and article information

            Journal
            Computational Linguistics
            Computational Linguistics
            MIT Press - Journals
            0891-2017
            1530-9312
            December 2012
            December 2012
            : 38
            : 4
            : 799-825
            10.1162/COLI_a_00111
            © 2012

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