通过听觉模型处理的语音信号中相互信息的神经估计
Donghoon Shin1,2, Hyung Soon Kim1
1Department of Electronics Engineering, Pusan National University, Busan, South Korea.
The Journal of the Acoustical Society of America
|January 21, 2025
概括
研究人员使用神经估计器量化了语音信号信息. 单音比辅音含有更多的相互信息,听觉处理影响信息内容.
科学领域:
- 语音处理 语音处理
- 信息理论是信息理论.
- 听觉神经科学 听觉神经科学
背景情况:
- 语音中的信息量化对于语音技术和感知至关重要.
- 在语音信号中直接测量相互信息是具有挑战性的.
- 机器学习的进步使得数据驱动的相互信息估计成为可能.
研究的目的:
- 通过神经相互信息估计器估计语音信号的信息内容.
- 调查听觉处理,特别是Mel尺度过和动态范围截断如何影响信息内容.
主要方法:
- 语音信号使用Mel尺度过器银行进行细分和压缩.
- 过器银行输出被截断,以模拟审计系统的动态范围.
- 使用神经估计器来量化处理信号中的相互信息.
主要成果:
- 使用Mel尺度过器银行的数据压缩保留了重要的信息.
- 相互信息在语音类别之间有所不同,元音显示的内容高于辅音.
- 听觉模型的动态范围减少导致语音信号中的信息减少.
结论:
- 神经估计器提供了一种可行的方法来量化语音中的信息.
- 听觉处理阶段显著影响语音信号传递的信息.
- 了解信息内容是开发先进语音技术的关键.
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