SM2+在使用稀疏编码方法提取和评估具有生态意义的声景成分中的应用
Abstract
Passive acoustic monitoring is emerging as a promising non-invasive proxy for ecological complexity with potential as a tool for remote assessment and monitoring (Sueur & Farina, 2015). Rather than attempting to recognise species-specific calls, either manually or automatically, there is a growing interest in evaluating the global acoustic environment. Positioned within the conceptual framework of ecoacoustics, a growing number of indices have been proposed which aim to capture communitylevel dynamics by (e.g., Pieretti, Farina & Morri, 2011; Farina, 2014; Sueur et al., 2008b) by providing statistical summaries of the frequency or time domain signal. Although promising, the ecological relevance and efficacy as a monitoring tool of these indices is still unclear. In this paper we suggest that by virtue of operating in the time or frequency domain, existing indices are limited in their ability to access key structural information in the spectro-temporal domain. Alternative methods in which time-frequency dynamics are preserved are considered. Sparse-coding and source separation algorithms (specifically, shift-invariant probabilistic latent component analysis in 2D) are proposed as a means to access and summarise time-frequency dynamics which may be more ecologically-meaningful.
摘要：
被动声学监测正在成为一种有前景的非侵入性生态复杂性指标，有可能成为远程评估和监测的工具（Sueur&Farina，2015）。人们对评估全球声环境的兴趣日益浓厚，而不是试图手动或自动识别特定物种的叫声。在生态声学的概念框架内，越来越多的指标被提出，旨在通过提供频域或时域信号的统计摘要来捕捉社区层面的动态（例如，Pieretti、Farina和Morri，2011；Farina，2014；Sueur等人，2008b）。尽管前景光明，但作为这些指标的监测工具的生态相关性和有效性仍不清楚。在本文中，我们提出，由于在时域或频域中操作，现有索引在访问光谱时域中的关键结构信息的能力有限。考虑了保留时频动态的替代方法。稀疏编码和源分离算法（特别是2D中的移位不变概率潜在分量分析）被提出作为访问和总结时频动态的一种手段，这可能更具生态意义。
关键词：SM2+声学记录器，Wildlife Acoustics，野生动物声学记录，动物被动声学监测，声景生态学、快速生物多样性评估、生态声学、自动化方法、稀疏编码、声学生态位假说、概率潜在成分分析
