Unsupervised Topic Identification by Integrating Linguistic and Visual Information Based on Hidden Markov Models


This paper presents an unsupervised topic identification method integrating linguistic and visual information based on Hidden Markov Models (HMMs). We employ HMMs for topic identification, wherein a state corresponds to a topic and various features including linguistic, visual and audio information are observed. Our experiments on two kinds of cooking TV… (More)


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