Bayesian Language Model based on Mixture of Segmental Contexts for Spontaneous Utterances with Unexpected Words

COLING 2016 Ryu TakedaKazunori Komatani

This paper describes a Bayesian language model for predicting spontaneous utterances. People sometimes say unexpected words, such as fillers or hesitations, that cause the miss-prediction of words in normal N-gram models... (read more)

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