Modeling Real-Time Interpersonal Interaction in Spoken Communication

当前的口语对话系统通常不便于交互。虽然人类对话者可以熟练地谈判和控制节奏，并流畅地发出理解、控制意图、态度等信号，但大多数对话系统处理这些交互维度的能力很差，如果有的话。缺乏这一点，对话往往生硬、笨拙和令人沮丧，往往需要仔细注意，而且往往效率低下。为了解决这些问题，本研究计划寻求开发和评估允许对话系统解释和生成非语言和其他态度和情感指示的技术，从而提高系统可用性的这些实时方面。PI在受控领域记录人与人之间的对话，分析人类使用的韵律和上下文线索。此外，他们试图将这些线索解释为表达互动的语用层面。其结果将是一个实时人际互动的模型，如口头对话所示。这一模式将有助于开发更可用的信息语音获取系统。这些发现还可能支持构建口语对话系统，以应对更具挑战性的对话类型，如教学、建议和销售。

Current spoken dialog systems are generally not pleasant to interact with. While human interlocutors can deftly negotiate and control pace, and smoothly signal understanding, control intentions, attitude, and so on, most dialog systems deal poorly, if at all, with these dimensions of interaction. Lacking this, dialogs tend to be stilted, awkward and frustrating, tend to demand careful attention, and tend to be time-inefficient. To address these problems, this research program seeks to develop and evaluate techniques that allow dialog systems to interpret and generate non-verbal and other indications of attitude and feeling, thereby improving these real-time aspects of system usability.The PIs are recording human-human dialogs in controlled domains, analyzing the prosodic and contextual cues that humans use. Further, they are seeking to interpret these cues as expressing pragmatic dimensions of the interaction. The result will be a model of real-time interpersonal interaction as manifested in spoken dialog. This model will be useful for the development of more usable systems for voice access to information. The findings may also support the construction of spoken dialog systems for more challenging dialog types, such as teaching, advising and selling.