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In this paper, a model is proposed to improve monophone-based connected word speech recognition for the Hindi language by utilizing the Hidden Markov Model (HMM). The model consists of hybrid subword units and domain-specific syntactic structures. The hybrid units contain both phoneme- and syllable-based subword units. As the syllable-based subword units cover a larger acoustic span, contextual effects are reduced. The syllable-based acoustic units are applied for modelling only nasal sound in the hybrid model for improving the recognition score of a nasal sound. Further, improvement is proposed using syntactic structures in the grammar definition during the recognition process. Using the domain-specific syntactic structures in the grammar, the search space for the recognizer is reduced; consequently, the performance of the system is improved. For example, two grammar definitions (gram1) with no …