Pregled bibliografske jedinice broj: 1005941
Machine Listening for Park Soundscape Quality Assessment
Machine Listening for Park Soundscape Quality Assessment // Acta Acustica united with Acustica, 104 (2018), 1; 121-130 doi:10.3813/aaa.919152 (međunarodna recenzija, članak, znanstveni)
CROSBI ID: 1005941 Za ispravke kontaktirajte CROSBI podršku putem web obrasca
Naslov
Machine Listening for Park Soundscape Quality Assessment
Autori
Boes, Michiel ; Filipan, Karlo ; De Coensel, Bert ; Botteldooren, Dick
Izvornik
Acta Acustica united with Acustica (1610-1928) 104
(2018), 1;
121-130
Vrsta, podvrsta i kategorija rada
Radovi u časopisima, članak, znanstveni
Ključne riječi
Machine listening ; Urban sound environment
Sažetak
The increasing importance attributed to soundscape quality in urban design generates a need for a system for automatic quality assessment that could be used for example in monitoring. In this work, the possibility for using machine listening techniques for this purpose is explored. The outlined approach detects the presence of particular sounds in a human-inspired way, and therefore allows to draw conclusions about how soundscapes are perceived. The system proposed in this paper consists of a partly recurrent artificial neural network modified to incorporate human attention mechanisms. The network is trained on sounds recorded in typical urban parks in the city of Antwerp, and thus becomes an auditory object creation and classification system particularly tuned to this context. The system is used to analyze a continuous sound level recording in different parks, resulting in a prediction of sounds that will most likely be noticed by a park visitor. Finally, it is shown that these indicators for noticed sounds allow to construct more powerful models for soundscape quality as reported in a survey with park visitors than indicators that are more regularly used in soundscape research.
Izvorni jezik
Engleski
Znanstvena područja
Elektrotehnika, Računarstvo
Citiraj ovu publikaciju:
Časopis indeksira:
- Current Contents Connect (CCC)
- Web of Science Core Collection (WoSCC)
- Science Citation Index Expanded (SCI-EXP)
- SCI-EXP, SSCI i/ili A&HCI
- Scopus