Ren Yao, Johnson Michael T, Tao Jidong
Speech and Signal Processing Laboratory, Marquette University, P.O. Box 1881, Milwaukee, Wisconsin 53233-1881, USA.
J Acoust Soc Am. 2008 Jul;124(1):316-27. doi: 10.1121/1.2932070.
A significant and often unavoidable problem in bioacoustic signal processing is the presence of background noise due to an adverse recording environment. This paper proposes a new bioacoustic signal enhancement technique which can be used on a wide range of species. The technique is based on a perceptually scaled wavelet packet decomposition using a species-specific Greenwood scale function. Spectral estimation techniques, similar to those used for human speech enhancement, are used for estimation of clean signal wavelet coefficients under an additive noise model. The new approach is compared to several other techniques, including basic bandpass filtering as well as classical speech enhancement methods such as spectral subtraction, Wiener filtering, and Ephraim-Malah filtering. Vocalizations recorded from several species are used for evaluation, including the ortolan bunting (Emberiza hortulana), rhesus monkey (Macaca mulatta), and humpback whale (Megaptera novaeanglia), with both additive white Gaussian noise and environment recording noise added across a range of signal-to-noise ratios (SNRs). Results, measured by both SNR and segmental SNR of the enhanced wave forms, indicate that the proposed method outperforms other approaches for a wide range of noise conditions.
在生物声学信号处理中，一个重大且常常不可避免的问题是由于不利的录音环境而存在背景噪声。本文提出了一种新的生物声学信号增强技术，该技术可用于广泛的物种。该技术基于使用特定物种的格林伍德尺度函数的感知缩放小波包分解。在加性噪声模型下，使用与用于人类语音增强的技术类似的谱估计技术来估计纯净信号小波系数。将该新方法与其他几种技术进行了比较，包括基本带通滤波以及经典语音增强方法，如谱减法、维纳滤波和埃夫拉伊姆 - 马拉滤波。从几种物种记录的发声用于评估，包括圃鹀（Emberiza hortulana）、恒河猴（Macaca mulatta）和座头鲸（Megaptera novaeanglia），在一系列信噪比（SNR）下添加加性高斯白噪声和环境录音噪声。通过增强波形的SNR和分段SNR测量的结果表明，在广泛的噪声条件下，所提出的方法优于其他方法。
