SM2+在使用稀疏編碼方法提取和評估具有生態意義的聲景成分中的應用
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：
被動聲學監測正在成為一種有前景的非侵入性生態復雜性指標，有可能成為遠程評估和監測的工具（Sueur&Farina，2015）。人們對評估全球聲環境的興趣日益濃厚，而不是試圖手動或自動識別特定物種的叫聲。在生態聲學的概念框架內，越來越多的指標被提出，旨在通過提供頻域或時域信號的統計摘要來捕捉社區層面的動態（例如，Pieretti、Farina和Morri，2011；Farina，2014；Sueur等人，2008b）。盡管前景光明，但作為這些指標的監測工具的生態相關性和有效性仍不清楚。在本文中，我們提出，由于在時域或頻域中操作，現有索引在訪問光譜時域中的關鍵結構信息的能力有限。考慮了保留時頻動態的替代方法。稀疏編碼和源分離算法（特別是2D中的移位不變概率潛在分量分析）被提出作為訪問和總結時頻動態的一種手段，這可能更具生態意義。
關鍵詞：SM2+聲學記錄器，Wildlife Acoustics，野生動物聲學記錄，動物被動聲學監測，聲景生態學、快速生物多樣性評估、生態聲學、自動化方法、稀疏編碼、聲學生態位假說、概率潛在成分分析
