Effective Spoken Language Labeling with Deep Recurrent Neural Networks

Marco Dinarelli
Marco Dinarelli

arXiv: Computation and Language, Volume abs/1706.06896, 2017.

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Abstract:

Understanding spoken language is a highly complex problem, which can be decomposed into several simpler tasks. In this paper, we focus on Spoken Language Understanding (SLU), the module of spoken dialog systems responsible for extracting a semantic interpretation from the user utterance. The task is treated as a labeling problem. In the...More

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