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Sentiment-Driven Breakdown Detection Model Using Contextual Embedding ElMo

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Advanced Information Networking and Applications (AINA 2021)

Part of the book series: Lecture Notes in Networks and Systems ((LNNS,volume 225))

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Abstract

The recent rapid developments in neural networks have stimulated significant performance progress in detecting breakdown in dialogue. The existing research focuses on detecting breakdown from the data label using different features such as word similarity and topic transition; however, these features are insufficient to capture contextual features. Therefore, we used ELMo language model to extract the contextual feature to help to detect the breakdown which faces a challenge due to the basis of human opinion. Another crucial challenge facing breakdown detection is the lack annotated dataset. To take this challenge we used sentiment as the data label with contextualized ELMo embedding model to detect the breakdown in dialogue. The model was evaluated with state-of-the-art models and the results shows the proposed model outperforms other models.

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Author information

Authors and Affiliations

  1. School of Computer Science, Faculty of Engineering and Information Technology, University of Technology Sydney, Sydney, Australia

    Ebtesam Hussain Almansor & Farookh Khadeer Hussain

  2. Community College, Najran University, Najran, Saudi Arabia

    Ebtesam Hussain Almansor

Authors
  1. Ebtesam Hussain Almansor
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  2. Farookh Khadeer Hussain
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Corresponding author

Correspondence to Ebtesam Hussain Almansor .

Editor information

Editors and Affiliations

  1. Department of Information and Communication Engineering, Fukuoka Institute of Technology, Fukuoka, Japan

    Leonard Barolli

  2. Department of Computer Science, Ryerson University, Toronto, ON, Canada

    Isaac Woungang

  3. Faculty of Business Administration, Rissho University, Tokyo, Japan

    Tomoya Enokido

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Almansor, E.H., Hussain, F.K. (2021). Sentiment-Driven Breakdown Detection Model Using Contextual Embedding ElMo. In: Barolli, L., Woungang, I., Enokido, T. (eds) Advanced Information Networking and Applications. AINA 2021. Lecture Notes in Networks and Systems, vol 225. Springer, Cham. https://doi.org/10.1007/978-3-030-75100-5_15

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