Language Technologies Thesis Proposal

  • Gates Hillman Centers
  • Traffic21 Classroom 6501
  • RAN ZHAO
  • Ph.D. Student
  • Language Technologies Institute
  • Carnegie Mellon University
Thesis Proposals

Socially-Aware Dialog System

In the past two decades, spoken dialog systems, such as those commonly found in cellphones and other interactive devices, have emerged as a key factor in human-computer interaction. For instance, Apple’s Siri, Microsoft’s Cortana, and Amazon’s Alexa help human users complete tasks more efficiently. However, research in this area has yet to produce dialog systems that build interpersonal closeness over the course of a conversation along with carrying out the task. This project attempts to address that shortcoming. Specifically, research in computational linguistics (Bickmore and Cassell, 1999) has shown that people pursue multiple conversational goals in dialog, which include those that fulfill propositional functions to contribute information to the dialog; those that fulfill interactional functions to manage conversational turn-taking; and those that fulfill interpersonal functions to manage the relationship between interlocutors. Although spoken dialog systems have greatly advanced in modeling the propositional and, to a lesser extent, interactional functions of human communication, these systems fall short in replicating the interpersonal functions of conversation. We propose that this interpersonal deficiency is due to a lack of models of interpersonal goals and strategies in human communication.

As dialog systems become more common and are used more frequently as interfaces to search and other computing tasks, propositional content and interactional content will not suffice. In this thesis, therefore, we address these challenges by proposing a socially-aware intelligent framework that exploits a path to systematically generate dialogs that fulfill interpersonal functions. In (Zhao et al., 2014a), we clarify that a socially-aware intelligent framework can explain how humans in dyadic interactions build, maintain, and tear down social bonds through specific conversational strategies that fulfill specific social goals and that are instantiated in particular verbal and nonverbal behaviors. In order to operationalize this framework, we argue that four capabilities are needed to achieve a socially-aware intelligent system. The system must (1) automatically infer human users’ social intention by recognizing their social conversational strategies, (2) accurately estimate social dynamics by observing dyadic interactions, (3) reason through appropriate conversational strategies while accounting for both the task goal and social goal, and (4) realize surface-level utterances that blend task and social conversation. Our socially-aware dialog system focuses on blended conversations that mix a goaloriented task with social chat. As a proof of concept, we have induced a modularbased socially-aware personal assistant for a conference.

Finally, we propose to apply our socially-aware intelligent framework in negotiation dialog. We formulate a two-phase method to blend negotiation utterance with social conversation. Our pilot study shows that the system can facilitate negotiation by building a social bond with a human user.

Thesis Committee:
Alexander I. Rudnicky, (Chair)
Alan W Black (Co-Chair)
Louis-Philippe Morency
Amanda Stent (Bloomberg)

Copy of Thesis Proposal

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