@article {Murai:2018:0736-2935:4375,
title = "Active Sound Quality Control for Subjective Preference",
journal = "INTER-NOISE and NOISE-CON Congress and Conference Proceedings",
parent_itemid = "infobike://ince/incecp",
publishercode ="ince",
year = "2018",
volume = "258",
number = "3",
publication date ="2018-12-18T00:00:00",
pages = "4375-4383",
itemtype = "ARTICLE",
issn = "0736-2935",
url = "https://ince.publisher.ingentaconnect.com/content/ince/incecp/2018/00000258/00000003/art00041",
author = "Murai, Kenta and Ishimitsu, Shunsuke",
abstract = "In recent years, the engine-sound control method has shifted from noise reduction to sound design. Therefore, we have proposed a method to design the engine sound using active sound quality control (ASQC) based on ANC technology. The auditory impressions of engine sound controlled by
ASQC were investigated using psychoacoustic measurements. When the reduction level increased, the preference was decreased or increased from the reference sound. Further, when the amplification-level increased, the preference was decreased from the reference sound. These results indicated
that the control corresponding to the individual is important for improvements in auditory impressions. To solve these problems, ASQC was developed to adjust to individual preferences. The individual preferences of sound were connected to each driver's driving pattern using deep learning.
Thus, we developed an ASQC system, which enables the automatic generation of individual sound preferences.",
}