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A Study of Web-Based Oral Activities Enhanced By Automatic Speech Recognition for EFL College Learning

机译:基于网络口语活动的语音自动识别技术在大学英语学习中的应用研究

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Recently, a promising topic in computer-assisted language learning is the application of Automatic Speech Recognition (ASR) technology for assisting learners to engage in meaningful speech interactions. Simulated real-life conversation supported by the application of ASR has been suggested as helpful for speaking. In this study, a web-based conversation environment called CandleTalk, which allows learners to seemingly talk with the computer, was developed to help EFL learners receive explicit speech acts training that leads to better oral competence. CandleTalk is equipped with an ASR engine that judges whether learners provide appropriate input. Six speech acts are presented as the foci of the materials with local cultural information incorporated as the content of the dialogues to enhance student motivation. The materials were put to use on 29 English major and 20 non-English major students in order to investigate their learning outcome and perception in an EFL context. Oral proficiency assessment using the format of the Discourse Completion Test (DCT) given before and after the use of CandleTalk and an evaluation questionnaire were two instruments used for data collection. The results of the study showed that the application of ASR was helpful for the college freshmen in the teaching of speech acts, particularly for the non-English major students. Most learners perceived positively toward the instruction supported with speech recognition.
机译:最近,计算机辅助语言学习中的一个有前途的主题是自动语音识别(ASR)技术的应用,该技术可帮助学习者进行有意义的语音交互。有人建议通过ASR应用程序支持的模拟现实生活中的对话对讲话很有帮助。在这项研究中,开发了一个称为CandleTalk的基于Web的对话环境,该环境使学习者似乎可以与计算机交谈,以帮助EFL学习者接受明确的言语行为训练,从而提高口语能力。 CandleTalk配备了ASR引擎,用于判断学习者是否提供适当的输入。介绍了六种言语行为作为教材的重点,并结合了当地文化信息作为对话的内容,以增强学生的学习动机。这些材料被用于29名英语专业和20名非英语专业学生,以调查他们在EFL语境下的学习成果和看法。使用CandleTalk之前和之后进行的话语能力测验(DCT)格式进行口语能力评估和评估问卷是用于收集数据的两种工具。研究结果表明,ASR的应用有助于大学新生在言语行为教学中,特别是对于非英语专业的学生。大多数学习者对语音识别支持的教学抱有积极的看法。

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