Machine listening for park soundscape quality assessment
| Autor: | Bert De Coensel, Dick Botteldooren, Karlo Filipan, Michiel Boes |
|---|---|
| Jazyk: | angličtina |
| Rok vydání: | 2018 |
| Předmět: |
Soundscape
Technology and Engineering Acoustics and Ultrasonics Computer science media_common.quotation_subject Context (language use) URBAN SOUNDSCAPES 01 natural sciences 060404 music NOISE Human–computer interaction Perception 0103 physical sciences Quality (business) 010301 acoustics media_common Machine listening PERCEPTION Visitor pattern AUDITORY ATTENTION Urban design Urban sound environment 06 humanities and the arts MODEL Construct (philosophy) 0604 arts Music |
| Zdroj: | ACTA ACUSTICA UNITED WITH ACUSTICA |
| ISSN: | 1610-1928 1861-9959 |
| Popis: | 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. |
| Databáze: | OpenAIRE |
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