后过器用于双通道语音增强使用连贯性和基于统计模型的噪声估计.
Sein Cheong1, Minseung Kim1, Jong Won Shin1
1School of Electrical Engineering and Computer Science, Gwangju Institute of Science and Technology, Gwangju 61005, Republic of Korea.
本研究介绍了一种新的语音增强后过器,使用连贯性和统计模型进行准确的噪音估计. 该方法可以在扩散噪声中提高语音质量,而不会通过方向干扰降低语音质量.
科学领域:
- 信号处理 信号处理
- 声学 声学 在声学方面
- 语音技术 语言技术
背景情况:
- 多通道语音增强系统依赖于空间波器和后波器来降低噪音.
- 准确估计剩余噪声功率光谱密度 (PSD) 对于有效的后过至关重要.
研究的目的:
- 为多通道语音增强提出一种新的后过器.
- 开发基于连贯性和统计模型的后续语音存在概率 (SPP) 和噪音PSD的新估计器.
主要方法:
- 以后使用麦克风信号之间的连贯性建模SPP,并将其与基于统计模型的SPP相结合.
- 使用伪相干性推导出基于相干性的噪声PSD估计器,考虑光束转换器效应.
- 结合基于连贯性和基于统计模型的噪声PSD估计器与拟议的SPP.
- 修改了光谱增益函数,以纳入拟议的SPP.
主要成果:
- 与现有方法相比,拟议的方法实现了更准确的噪声PSD估计.
- 实验结果显示,在分散的噪音环境中,语音质量 (PESQ) 评分的感知评估得到了改善.
- 在有方向干扰的情况下,该方法不会降低语音质量.
结论:
- 提出的基于连贯性的方法提高了语音增强中的噪声估计准确性.
- 新型后过器在各种噪音条件下有效地提高了语音质量.
- 利用连贯信息为先进的语音增强系统提供了一个强大的策略.
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