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- W2294799286 abstract "Dialogue act recognition commonly relies on lexical, syntactic, prosodic and/or dialogue history based features. However, few approaches exploit semantic information. The main goal of this paper is thus to propose semantic features and integrate them into ai¾źdialogue act recognition task to improve the recognition score. Three different feature computation approaches are proposed, evaluated and compared: Latent Dirichlet Allocation and the HAL and COALS semantic spaces. An interesting contribution is that all the features are created without any supervision. These approaches are evaluated on a Czech dialogue corpus. We experimentally show that all proposed approaches significantly improve the recognition accuracy." @default.
- W2294799286 created "2016-06-24" @default.
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- W2294799286 date "2015-01-01" @default.
- W2294799286 modified "2023-09-27" @default.
- W2294799286 title "Semantic Features for Dialogue Act Recognition" @default.
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- W2294799286 doi "https://doi.org/10.1007/978-3-319-25789-1_15" @default.
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