用于阅读增强和诊断的计算机鉴别声学工具:开发和试点测试

Ricardo A. Catanghal, Joe-Ann B. Catanghal
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引用次数: 0

摘要

语言是人类之间一种简单而有效的交流方式,目前我们不仅与身体相连,而且与生活中的许多设备相连。几十年来,设计一台模仿人类能力的机器,尤其是在倾听和回应人类话语方面,一直困扰着工程师和科学家。本文对声学方面的文献进行了深入的分析,提出了自动语音识别的总体架构,包括声学前端、声学模型、语言模型和解码器。在语音识别系统的测试实施中,使用了技术接受模型,并使用了研究后系统可用性问卷(PSSUQ)来收集初始用户的反馈。此外,实验对选定的学生进行了为期四周的设置,并分为两组控制和非控制。结果是令人鼓舞的两项措施:可接受性和执行,鼓励在更广泛的样本中进一步研究。这将有助于阅读教学,特别是在疫情期间,面对面交流是有限的。
本文章由计算机程序翻译,如有差异,请以英文原文为准。
Computer Discriminative Acoustic Tool for Reading Enhancement and Diagnostic: Development and Pilot Test
Speech is a simple and effective method of communication between humans, currently we are not only connected physically but also to the many devices in our life. Designing a machine that mimics human capabilities, especially in listening and responding to uttering words of humans have puzzled engineers and scientist for decades. In this paper, a thorough analysis of the literature on the acoustic was conducted, and the general architecture of the automatic speech recognition is presented consisting of acoustic front-end, acoustic model, language model, and decoder. In the test implementation of the speech recognition system, the Technology Acceptance Model was utilized, and Post-Study System Usability Questionnaire (PSSUQ) was used in gathering the feedback of the initial users. Further, experimentation to selected students was administered in a four-week setting and divided into two groups controlled and uncontrolled. The result is encouraging in the two measures: acceptability and implementation, further study is encouraged in a broader sample is sought. This will be helpful in teaching reading especially in this time of pandemic where face-to-face is limited.
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