Psychoacoustic Approach to Noise: Evaluation, Estimation and Design
A special issue of Applied Sciences (ISSN 2076-3417). This special issue belongs to the section "Acoustics and Vibrations".
Deadline for manuscript submissions: closed (31 March 2022) | Viewed by 11087
Special Issue Editor
Interests: psychoacoustics; sound quality; environmental acoustics; soundscape; sound design
Special Issues, Collections and Topics in MDPI journals
Special Issue Information
Dear Colleagues,
Noise generally has an adverse effect on people and the environment. To address such problems, noise reduction should be considered as the first countermeasure. Also the psychoacoustic approach is useful for obtaining effective improvements and optimal designs to reduce adverse effects of noise. This approach has long been introduced with proven success in the automotive industry. We can now employ various methodologies for noise evaluation, including the evaluation grid method as well as traditional techniques such as semantic differential, paired comparison and methods in psychophysics. Physiological approaches are still important, although they have been adopted to evaluate the effects of noise on humans. To explore new designs related to noise, machine learning, which has shown remarkable development in recent years, may be effective. On the other hand, to evaluate the sonic environment (soundscape), the new methodology has been provided as international standards (i.e., ISO 12913-1:2014, ISO/TS 12913-2:2018). As above, a psychoacoustic approach for handling noise has been developed by incorporating techniques from various disciplines. From such a background, the present Special Issue aims to introduce recent developments in the psychoacoustic approach and their applications for noise. The editor hopes that this Special Issue will inspire further activity in the field of noise evaluation.
Research topics of interest include, but are not limited to, the following:
- Product sound quality
- Psychoacoustic-based design of noise
- Physiology-based design of noise
- Sound quality metrics
- Soundscape
- Sonic environment
- Application of machine learning to sound design
- Analysis by synthesis of noise
Dr. Masayuki Takada
Guest Editor
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Keywords
- noise
- psychoacoustics
- product sound quality
- sound quality metrics
- physiological effects
- soundscape
- environmental acoustics
- machine learning
- sound synthesis
- sound design
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