Deep learning techniques for noise annoyance detection: Results from an intensive workshop at the Alan Turing Institute
Advancements in AI and ML have enabled us to combine automated sound source
recognition and deep learning models for predicting subjective soundscape perception. We
held a multidisciplinary, cross-institutional Data Study Group (DSG) to investigate how
sound source information could be incorporated into deep learning models for predicting
urban noise annoyance. We used a large-scale dataset of 2980 15-s recordings paired with
12 210 annoyance ratings (from 1 to 10) and sound source labels. A total of 14 neural …
recognition and deep learning models for predicting subjective soundscape perception. We
held a multidisciplinary, cross-institutional Data Study Group (DSG) to investigate how
sound source information could be incorporated into deep learning models for predicting
urban noise annoyance. We used a large-scale dataset of 2980 15-s recordings paired with
12 210 annoyance ratings (from 1 to 10) and sound source labels. A total of 14 neural …