使用合成语音和自动语音识别测试语音中的句子识别
Lauren Calandruccio1, Dani Weidman2, Aja Leatherwood1
1Department of Psychological Sciences, Case Western Reserve University, Cleveland, OH.
Journal of speech, language, and hearing research : JSLHR
|November 10, 2025
概括
这项研究探讨了使用人工智能进行语音噪音识别测试. 结果表明,合成语音和机器评分对听力学研究具有前景,人类和机器评估之间的高度一致.
科学领域:
- 听力学 听力学是指听力学.
- 语音科学 语言科学
- 人工智能的人工智能
背景情况:
- 在听力学和听力研究中,语音噪音识别至关重要.
- 目前的方法使用人类记录和测试人员,耗时.
- 人工智能为自动化刺激生成和得分提供了潜力.
研究的目的:
- 用合成和人类语音来评估面具句子识别.
- 为了比较人类和机器评分方法用于语音噪音任务.
- 评估AI在听力学评估中的可行性.
主要方法:
- 听力正常的年轻人完成了语音在噪音中的任务.
- 开放式的句子以-6dB的信号噪声比率呈现.
- 人类和自动语音识别 (ASR) 均对听者的表现进行了评分.
主要成果:
- 在人类和合成说话者之间,语音可理解性各不相同.
- 对于两个语音类型来说,识别的个体差异是相似的.
- 人类和ASR评分显示高达成一致 (~98%).
结论:
- 合成语音可能提供更大的可理解性一致性.
- 人类评分对开放式句子更准确,但ASR显示了密切的协议.
- 人工智能工具显示了自动化语音在噪音中识别评估的潜力.
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