Implementing discourse-gating tasks to study the timing of speech act recognition

Kathleen Bardovi-Harlig , Yunwen Su
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Abstract

This paper presents the development of two novel discourse-gating tasks to investigate the processing of pragmatic information, namely, the timing of the recognition of genuine (sincere) and ostensible (transparently insincere) refusals in Chinese and provides preliminary validity evidence for the tasks. Gating tasks were introduced to investigate spoken word recognition and have been successfully extended to spoken language processing, most notably sentences. Following Grosjean's (1996) observation that gating tasks could be used to investigate a variety of linguistic features, we extended the gating tasks to spoken discourse using turns as gates. The open-prediction gating task allows participants to make a single prediction about the outcome of each of 12 recorded conversations as soon as they can. The fixed-prediction gating task asks participants to make predictions at regular intervals while listening to a second set of 12 conversations. One hundred and seven participants (60 L1 speakers and 47 third- and fourth-year learners of Chinese) were recruited to test the tasks. The tasks reveal a lag in speech-act identification not found when retrospective speech-act identification tasks are used. The fixed-prediction task additionally reveals alternatives that are considered during processing. The paper discusses the benefits of the discourse gating tasks and the merits of each, the quantitative and qualitative evidence for the tasks, and future directions for discourse gating tasks.

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实施话语门控任务,研究言语行为识别的时间安排
本文介绍了两个新颖的话语门控任务的开发情况,以研究语用信息的处理,即识别汉语中真正的(真诚的)和表面的(明显不真诚的)拒绝的时间,并提供了任务的初步有效性证据。门控任务是为研究口语单词识别而引入的,现已成功扩展到口语处理,尤其是句子。根据 Grosjean(1996 年)的观察,门控任务可用于研究各种语言特点,因此我们将门控任务扩展到以转弯为门控的口语话语。开放式预测门控任务允许参与者尽快对 12 个录制对话中的每个对话结果进行单一预测。固定预测门控任务要求参与者在聆听第二组 12 个对话时每隔一定时间进行预测。我们招募了 107 名参与者(60 名第一语言使用者和 47 名三、四年级汉语学习者)来测试这些任务。这些任务揭示了在使用回顾性言语行为识别任务时未发现的言语行为识别滞后现象。此外,固定预测任务还揭示了在处理过程中考虑的备选方案。本文讨论了话语门控任务的益处和每个任务的优点、任务的定量和定性证据以及话语门控任务的未来发展方向。
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