Abstract
The recent abundance of conversational data on the Web and elsewhere calls for effective NLP systems for dialogue understanding. Complete utterance-level understanding often requires context understanding, partly defined by the nearby utterances and by the user intention and background. In recent years, a number of context-aware approaches have been proposed for various utterance-level dialogue understanding tasks. In this paper, we explore and quantify the role of context for different aspects of a dialogue, namely emotion, dialogue act, and intent identification, using stateof-the-art dialogue 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 context factors that have immediate implications on different aspects of a dialogue. Such insights may inspire more effective dialogue understanding models and provide support for future text generation approaches.