非线性语音现象和语音可理解性
Andrey Anikin1, David Reby2,3, Katarzyna Pisanski2,4
1Division of Cognitive Science, Department of Philosophy, Lund University, Box 192, SE-221 00, Lund, Sweden.
概括
人类语音的可理解性取决于声音的稳定性,不一定是音质. 非线性语音现象 (NLP) 可以改善元音感知,但发音中断会降低清晰度,这表明对演化为语音的NLP有更好的控制.
科学领域:
- 进化生物学是进化的生物学.
- 语音科学是一种语言科学.
- 生物声学是一种生物声学.
背景情况:
- 人类拥有比其他类人猿更简单的声器,缺乏声膜和气囊.
- 假设这种简化是对语音的适应,少一些非线性声学现象 (NLP) 创造了一个稳定的声源.
- 关于NLP降低语音可理解性的假设得到了语音障碍的研究的支持,但缺乏直接的实验测试.
研究的目的:
- 实验测试非线性声学现象 (NLP) 对语音可理解性的影响.
- 为了确定语音稳定性或音质质量是否对语音感知更为关键.
- 研究不同类型的NLP如何影响元音,单词和句子的可理解性.
主要方法:
- 在合成和录制的语音刺激中操纵NLP,包括元音,单词和句子.
- 通过歧视任务评估语音可理解性.
- 分析连续NLP (亚和声,振幅调制,混乱) 和突然NLP (发声中断,音调跳跃) 的影响.
主要成果:
- 语音稳定性,而不是音质质量,对于语音可理解性至关重要.
- 持续的NLP可以通过揭示形式过渡来增强高音调声音中的母音感知.
- 使用连续NLP的粗略声音仍然可以理解,但发声中断和音调跳跃显著降低了可理解性.
结论:
- 非线性语音现象 (NLP) 在人类演化过程中并没有被消除,而是得到了更好的控制.
- 语音稳定是可理解性的关键因素,而某些NLP可以有益.
- 了解NLP的控制提供了对人类言语演变的见解.
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