1 |
Lee, Y. H., "Speech/Auido Processing based on Deep Learning," Journal of Broadcasting and Media Magazine, Vol. 22, No. 1, pp. 46-57, 2017.
|
2 |
Krizhevsky, A., Sutskever, I. and Hinton, G. E., "Imagenet classification with deep convolutional neural networks," Journal of Communications of the ACM, Vol. 60, No. 6, pp. 84-90, 2017.
DOI
|
3 |
Suh, S., Lim, W., Jeong, Y., Lee, T., & Kim, H. Y. "Dual CNN Structured Sound Event Detection Algorithm Based on Real Life Acoustic Dataset," Journal of Broadcast Engineering, Vol. 23, No. 6, pp. 855-865, 2018.
DOI
|
4 |
Hinton, G., et al., "Deep Neural Networks for Acoustic Modeling in Speech Recognition: The Shared Views of Four Research Groups," Journal of IEEE Signal Processing Magazine, Vol. 29, No. 6, pp. 82-97, 2012.
DOI
|
5 |
Lee, Y. H., Cho, C. S. and Kim, J. W., "Development of Automative Loudness Control Tecgnique based on Audio Contents Analysis using Deep Learning," Journal of Broadcasting and Media Magazine, pp. 42-43, 2018.
|
6 |
Hershey, S., Chaudhuri, S., Ellis, D., Gemmeke, J., Jansen, A. and Moore, R., "CNN architectures for large-scale audio classification," In Acoustics, Speech and Signal Processing (ICASSP), pp. 131-135, 2017.
|
7 |
Lee, S., Kim, G., Choi, S. "A Machine Learning Program for Impact Fracture Analysis," The Korean Society of Manufacturing Process Engineers, Vol. 20, No. 1, pp. 95-102, 2021.
DOI
|