Automated vocalization identification still fails under masking from geophony and anthrophony

Evidence

The automated identifications of animal vocalization using, for example, the hidden Markov model (HMM), dynamic time warping (DTW), or Gaussian mixture model (GMM), are procedures in quick improvement (Anderson et al. 1996; Kwan et al. 2004; Chen and Maher 2006; Deecke and Janik 2006; Sumervuo et al. 2006; Trifa et al. 2008), although at the present time these procedures can be used only for a few species that have a simple sound structure and for records of quality without the masking effects of geophonies (rain, wind) or anthrophonies (airplane noise, traffic noise, etc.). — Almo Farina, Soundscape Ecology, 2049

Categorization

• XREF: connects to: Song Scope frog identification failed on roughly half of recordings — Almo Farina, Soundscape Ecology: Principles,…, 2055; Automated Gabor-transform identification succeeded on 67 bird species but struggled with low-frequency-dominated songs — Almo Farina, Soundscape Ecology: Principles,…, 2054; Autonomous recording advanced but automatic sound identification remains unsolved — Almo Farina, Soundscape Ecology: Principles,…, 113