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Intent Detection System Based on Word Embeddings

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Artificial Intelligence: Methodology, Systems, and Applications (AIMSA 2018)

Abstract

Intent detection is one of the main tasks of a dialogue system. In this paper we present our intent detection system that is based on FastText word embeddings and neural network classifier. We find a significant improvement in the FastText sentence vectorization. The results show that our intent detection system provides state-of-the-art results on three English datasets outperforming many popular services.

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Notes

  1. 1.

    https://wit.ai/.

  2. 2.

    https://github.com/snipsco/nlu-benchmark.

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Acknowledgments

The research has been supported by the European Regional Development Fund within the project “Neural Network Modelling for Inflected Natural Languages” No. 1.1.1.1/16/A/215.

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Correspondence to Kaspars Balodis .

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Balodis, K., Deksne, D. (2018). Intent Detection System Based on Word Embeddings. In: Agre, G., van Genabith, J., Declerck, T. (eds) Artificial Intelligence: Methodology, Systems, and Applications. AIMSA 2018. Lecture Notes in Computer Science(), vol 11089. Springer, Cham. https://doi.org/10.1007/978-3-319-99344-7_3

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  • DOI: https://doi.org/10.1007/978-3-319-99344-7_3

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