On-Device Intelligence for Real-Time Audio Classification and Enhancement

Hwang I, Kim K, Kim S. On-Device Intelligence for Real-Time Audio Classification and Enhancement. J Audio Eng Soc. 2023;71(10):719-728. doi:10.17743/jaes.2022.0093

@article{Hwang2023_22243,
  author = {Hwang, Inwoo and Kim, Kibeom and Kim, Sunmin},
  title = {{On-Device Intelligence for Real-Time Audio Classification and Enhancement}},
  journal = {Journal of the Audio Engineering Society},
  volume = {71},
  number = {10},
  pages = {719--728},
  year = {2023},
  month = oct,
  publisher = {Audio Engineering Society},
  doi = {10.17743/jaes.2022.0093},
  url = {https://doi.org/10.17743/jaes.2022.0093}
}

TY  - JOUR
TI  - On-Device Intelligence for Real-Time Audio Classification and Enhancement
AU  - Hwang, Inwoo
AU  - Kim, Kibeom
AU  - Kim, Sunmin
T2  - Journal of the Audio Engineering Society
J2  - J. Audio Eng. Soc.
VL  - 71
IS  - 10
SP  - 719
EP  - 728
PY  - 2023
DA  - 2023/10/06
DO  - 10.17743/jaes.2022.0093
UR  - https://doi.org/10.17743/jaes.2022.0093
PB  - Audio Engineering Society
LA  - en
AB  - Audio enhancement is a signal processing method that improves the listening experience. Although most audio devices provide a variety of sound-enhancing effects, it is reported that very few people are active users of this feature. This lack of usability comes from insufficient sound improvement because of concerns about scene-rendering mismatch, which means that the processing applied to an unintended target may even damage the sound quality. The key solution to this problem is sound intelligence that provides an optimal sound effect with very low latency. The authors propose a real-time audio enhancement system based on a highly precise audio scene classifier using convolutional neural networks. The entire computation including convolutions is optimized for digital signal processing--level implementation, resulting in enhanced audio outputs for every audio frame.
ER  -