开发一种基于短语的语音识别测试,使用合成语音.
Saskia Ibelings1,2,3, Thomas Brand2,3, Esther Ruigendijk3,4
1Institute of Hearing Technology and Audiology, Jade University of Applied Sciences, Oldenburg, Germany.
Trends in hearing
|July 25, 2024
概括
开发了一种新的语音识别测试,使用合成短语来减少训练效应并扩展语音材料. 该测试的性能与现有的句子测试相提并论,显示了听力学研究和临床应用的潜力.
科学领域:
- 听力学 听力学是指听力学.
- 语音感知研究研究 语音感知研究
背景情况:
- 语音识别测试在听力学中对于临床和研究应用至关重要.
- 现有的测试经常受到训练效应和有限的语言材料的影响.
研究的目的:
- 开发一种新的语音识别测试,最大限度地减少训练效应.
- 用一个大型的模块化语音材料集创建一个测试.
主要方法:
- 从数据库中使用常见名词,形容词和无穷词构建了772个独特的短语.
- 为了提高效率,使用文本转化为语音系统合成短语.
- 评估了31名正常听力参与者在固定信号噪声比率 (SNR) 的测试.
主要成果:
- 实现了语音识别值 (SRT) 的中位数为-9.1 dB SNR,与现有的句子测试相匹配.
- 观察到的语音识别得分在短语之间变化高达4dB.
- 证明了每dB的心理测量功能的斜率为15个百分点,适合听力学.
结论:
- 开发的模块化语音材料系统有效地减少了训练效应.
- 新的测试是高效的,可以与当前的听力学标准相比较.
- 模块化方法在语音研究中提供了广泛的潜在应用.
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