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    Introducing a Hybrid Language Model for Improving Performance of Continuous Speech Recognition Systems

    , Ph.D. Dissertation Sharif University of Technology Bahrani, Mohammad (Author) ; Sameti, Hossein (Supervisor)
    Abstract
    The utilizing language model is one of the most effective methods for improving speech recognition performance. For speech recognition applications, several types of language models have been proposed for speech recognition applications that try to model some parts of language information, such as n-gram models, syntactic models, and semantic models. Although n-gram, syntactic and semantic models are able to model different structures that exist in natural language, they each only capture specific linguistic phenomena. None of them can simultaneously take into account all of language phenomena in a unified probabilistic framework. Recently, a number of semantic models called "latent topic...