Active Sound Design Development Based on the Harmonics of Main Order From Engine Sound

Moon S, Park S, Park D, Yun M, Chang K, Park D. Active Sound Design Development Based on the Harmonics of Main Order From Engine Sound. J Audio Eng Soc. 2020;68(7/8):532-544. doi:10.17743/jaes.2020.0044

@article{Moon2020_20889,
  author = {Moon, Soyoun and Park, Sunghwan and Park, Donggun and Yun, Myunghwan and Chang, Kyongjin and Park, Dongchul},
  title = {{Active Sound Design Development Based on the Harmonics of Main Order From Engine Sound}},
  journal = {Journal of the Audio Engineering Society},
  volume = {68},
  number = {7/8},
  pages = {532--544},
  year = {2020},
  month = jul,
  publisher = {Audio Engineering Society},
  doi = {10.17743/jaes.2020.0044},
  url = {https://doi.org/10.17743/jaes.2020.0044}
}

TY  - JOUR
TI  - Active Sound Design Development Based on the Harmonics of Main Order From Engine Sound
AU  - Moon, Soyoun
AU  - Park, Sunghwan
AU  - Park, Donggun
AU  - Yun, Myunghwan
AU  - Chang, Kyongjin
AU  - Park, Dongchul
T2  - Journal of the Audio Engineering Society
J2  - J. Audio Eng. Soc.
VL  - 68
IS  - 7/8
SP  - 532
EP  - 544
PY  - 2020
DA  - 2020/07/06
DO  - 10.17743/jaes.2020.0044
UR  - https://doi.org/10.17743/jaes.2020.0044
PB  - Audio Engineering Society
LA  - en
AB  - Most previous studies on active sound design (ASD) development proposed regression models based on psychoacoustic parameters for engine sound design. However, order-based parameters are required for a real ASD development, considering that an ASD system is controlled by order levels. In this paper, we propose a regression model utilizing order-level–based parameters that can be efficiently applied to ASD development. A jury test was conducted for 27 engine sound recordings using 36 participants with normal hearing ability to evaluate the level of affective adjectives. Then, acoustic parameters were measured from the engine sound recordings to identify the relationship between the adjectives and parameters. Finally, a regression model was derived through statistical analysis. The properties of the model were compared with those of models proposed in previous studies to verify its superiority. The proposed regression model can reduce the time and effort required for ASD development.
ER  -