Utterance-level Dialogue Understanding: An Empirical Study

• URL: http://arxiv.org/abs/2009.13902v5
• Date: Thu, 22 Oct 2020 11:16:56 GMT
• Title: Utterance-level Dialogue Understanding: An Empirical Study
• Authors: Deepanway Ghosal, Navonil Majumder, Rada Mihalcea, Soujanya Poria
• Abstract summary: This paper explores and quantify the role of context for different aspects of a dialogue. Specifically, we employ various perturbations to distort the context of a given utterance. This provides us with insights into the fundamental contextual controlling factors of different aspects of a dialogue.
• Score: 43.35258958775454
• License: http://creativecommons.org/licenses/by-sa/4.0/
• Abstract: The recent abundance of conversational data on the Web and elsewhere calls for effective NLP systems for dialog understanding. Complete utterance-level understanding often requires context understanding, defined by nearby utterances. In recent years, a number of approaches have been proposed for various utterance-level dialogue understanding tasks. Most of these approaches account for the context for effective understanding. In this paper, we explore and quantify the role of context for different aspects of a dialogue, namely emotion, intent, and dialogue act identification, using state-of-the-art dialog understanding methods as baselines. Specifically, we employ various perturbations to distort the context of a given utterance and study its impact on the different tasks and baselines. This provides us with insights into the fundamental contextual controlling factors of different aspects of a dialogue. Such insights can inspire more effective dialogue understanding models, and provide support for future text generation approaches. The implementation pertaining to this work is available at https://github.com/declare-lab/dialogue-understanding.

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