Active Sound Quality Control Based on Subjective Preference

2017-32-0034

11/05/2017

Features
Event
JSAE/SAE Small Engine Technologies Conference & Exhibition
Authors Abstract
Content
Recent years, ANC (Active Noise Control) technology has been paying attention. However, rather than the noise measures, the noise gives us the impression even running sound for motorcycles. That is, the control method of the engine sound is shifted from the noise reduction to sound design in each manufactures. Therefore, we proposed a method to design the engine sound using Active Sound Quality Control (ASQC) based on the ANC. Specifically, we proposed the algorithm amplifying and reducing the engine specific order components. From the simulation results, the engine specific order components can be amplified and reduced like an equalizer with the proposed algorithm. And, auditory impressions of engine sound controlled by ASQC were investigated using psychoacoustic measurements. 13 stimuli were obtained by applying ASQC for several order components to amplify or reduce their levels. Following stimuli were presented to 10 healthy volunteers with control for first-, second- and both first- and second-, order components to decrease or increase, respectively. The scale values of preference for each stimulus were obtained by Scheffe's paired comparison tests. When the reduction-level increased, the preference was decreased or increased from the reference sound. Also when the amplification-level increased, the preference was decreased from the reference sound. As the reason, it seems that reference sound pressure is felt to be sufficiently large. These results indicated that the control corresponding to the individual is important for improvements in auditory impressions.
Meta TagsDetails
DOI
https://doi.org/10.4271/2017-32-0034
Pages
4
Citation
Ishimitsu, S., Sagawa, T., Ito, T., Shibatani, N. et al., "Active Sound Quality Control Based on Subjective Preference," SAE Technical Paper 2017-32-0034, 2017, https://doi.org/10.4271/2017-32-0034.
Additional Details
Publisher
Published
Nov 5, 2017
Product Code
2017-32-0034
Content Type
Technical Paper
Language
English