How to Make Artificial Intelligence Recognise the Sounds that Contribute to Soundscape

Artificial intelligence (AI) is increasingly adept at recognising sounds and acoustic scenes, and generative AI can create meaningful narratives about them. However, in everyday environments, humans do not notice or pay attention to all sounds. This selective attention reflects nature's strategy to avoid overloading the energy-expensive human cognitive system. The biological mechanism of focusing on relevant sounds while filtering out irrelevant or repetitive stimuli is not well-matched in most current AI systems. Sounds stand out in the sonic environment due to their salience. A sound can be salient because of its (1) acoustic characteristics such as loudness, sharpness, and tonality; (2) semantic incongruity or unexpectedness; or (3) special meaning to an individual or society. Prior work focused on the first form of salience and integrated it into artificial soundscape analysis. Here, we report primarily on the latter forms. We identify sounds that would typically be recognised as foreground, salient sounds by a person. A processing layer is then added to the sound recognition system to identify these salient sounds and further process them into soundscape perception, thereby creating context awareness in the AI.

Authors

Institutions

Publication Details

Journal
NOISE-CON proceedings
Published
2025-10-22
DOI
https://doi.org/10.3397/in_2025_1075802
Primary Topic
Noise Effects and Management
Type
article
Field-Weighted Citation Impact
0.00
Controls
|||
ALL TIME
JAN
FEB
MAR
APR
MAY
JUN
JUL
AUG
SEP
OCT
article

How to Make Artificial Intelligence Recognise the Sounds that Contribute to Soundscape

Tomasz Grzywalski, Dick Botteldooren, Zhongju Yuan
NOISE-CON proceedings
Noise Effects and Management
article

How to Make Artificial Intelligence Recognise the Sounds that Contribute to Soundscape

Tomasz Grzywalski, Dick Botteldooren, Zhongju Yuan
article en

Abstract

Artificial intelligence (AI) is increasingly adept at recognising sounds and acoustic scenes, and generative AI can create meaningful narratives about them. However, in everyday environments, humans do not notice or pay attention to all sounds. This selective attention reflects nature's strategy to avoid overloading the energy-expensive human cognitive system. The biological mechanism of focusing on relevant sounds while filtering out irrelevant or repetitive stimuli is not well-matched in most current AI systems. Sounds stand out in the sonic environment due to their salience. A sound can be salient because of its (1) acoustic characteristics such as loudness, sharpness, and tonality; (2) semantic incongruity or unexpectedness; or (3) special meaning to an individual or society. Prior work focused on the first form of salience and integrated it into artificial soundscape analysis. Here, we report primarily on the latter forms. We identify sounds that would typically be recognised as foreground, salient sounds by a person. A processing layer is then added to the sound recognition system to identify these salient sounds and further process them into soundscape perception, thereby creating context awareness in the AI.

NOISE-CON proceedingsVol. 272(2)
Ghent University Hospital (BE)
Openalex Percentile: Top 56%
Noise Effects and Management
AI Navigator

Ask Laika to Summarize, Analyze, and Connect papers live on the map.

Summarize Papers & Methodologies

Extract key findings, datasets, and comparative methods across publications.

Benchmark Rankings & Visual Analytics

Rank top research institutions, authors, funders, topics, and journals by Field-Weighted Citation Impact (FWCI) and paper volume with instant charts.

Connect Distant Disciplines

Bridge topological clusters on the map to find hidden collaborative intersections.

How to Make Artificial Intelligence Recognise the Sounds that Contribute to Soundscape — Tomasz Grzywalski, Dick Botteldooren, et al. · NOISE-CON proceedings (2025) | TGRS Research Map | TGRS