Autonomous recording advanced but automatic sound identification remains unsolved

Evidence

With the use of digital technology, the expansion of magnetic memory and highly sophisticated microphones and amplifiers assembled into programmable devices for long-time autonomous (in terms of power supply) operation, the recording of soundscapes has made a leap forward during the last decennia. Despite these tremendous improvements, however, until now there have not been processes able to identify automatically every type of sound. This limitation poses problems in the identification of the components of a soundscape and largely reduces the possibility of efficient evaluation of the potentialities expressed in distinct sites. — Almo Farina, Soundscape Ecology, 113

Categorization

• QUESTION: The stated gap motivates later chi-index/automated analysis chapters — worth tracking how the method addresses auto-identification limits.
• XREF: connects to: Acoustic diversity does not measure biological diversity in birds — Almo Farina, Soundscape Ecology: Principles,…, 115; Automated vocalization identification still fails under masking from geophony and anthrophony — Almo Farina, Soundscape Ecology: Principles,…, 2049; Detecting sounds does not guarantee discriminating them, which also needs intact critical-band processing — David Howard, Jamie Angus, coustics and Psychoacoustics, 2352 (+1 more)

Broader Connections

• Automated vocalization identification still fails under masking from geophony and anthrophony #corroborates (0.92) — Almo Farina, Soundscape Ecology, 2049
• Polyphonic concurrent sources make automated music structure recognition difficult #exemplifies (0.82)
• Detecting sounds does not guarantee discriminating them, which also needs intact critical-band processing #expands (0.80) — David Howard, Jamie Angus, coustics and Psychoacoustics, 2352