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Noise Impact Suppression for Acoustic Complexity Index
The acoustic complexity index (ACI) remains relatively susceptible to noise in practice although it is designed with consideration for suppressing steady noise to a certain extent. This raises concerns about its reliability and overall effectiveness in acoustic ecological monitoring. In this work, a noise-robust strategy of ACI with the new-designed denoising acoustic complexity index (DACI) is introduced to address this issue. This improved version of ACI quantifies the variations of acoustic intensity within the power spectrogram instead of the magnitude one after a spectral subtraction based denoising procedure, such that it is more capable of capturing the intrinsic statistical features of biological communities in real-world soundscapes than ACI. Experimental results indicate that DACI maintains high numerical stability even at a low signal-to-noise ratio (SNR) of -20 dB and has a strong correlation with ACI under high SNR conditions. Consequently, this processing strategy is able to significantly extend the spatiotemporal application areas of noise-robust ACI variants without affecting the existing ecological interpretations and research accumulations of ACI.
Noise Impact Suppression for Acoustic Complexity Index
The acoustic complexity index (ACI) remains relatively susceptible to noise in practice although it is designed with consideration for suppressing steady noise to a certain extent. This raises concerns about its reliability and overall effectiveness in acoustic ecological monitoring. In this work, a noise-robust strategy of ACI with the new-designed denoising acoustic complexity index (DACI) is introduced to address this issue. This improved version of ACI quantifies the variations of acoustic intensity within the power spectrogram instead of the magnitude one after a spectral subtraction based denoising procedure, such that it is more capable of capturing the intrinsic statistical features of biological communities in real-world soundscapes than ACI. Experimental results indicate that DACI maintains high numerical stability even at a low signal-to-noise ratio (SNR) of -20 dB and has a strong correlation with ACI under high SNR conditions. Consequently, this processing strategy is able to significantly extend the spatiotemporal application areas of noise-robust ACI variants without affecting the existing ecological interpretations and research accumulations of ACI.
Noise Impact Suppression for Acoustic Complexity Index
Lai, Xiaotian (Autor:in) / Xu, Zhiyong (Autor:in) / Chen, Lei (Autor:in) / Zhao, Zhao (Autor:in)
15.11.2024
1436160 byte
Aufsatz (Konferenz)
Elektronische Ressource
Englisch
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