| Presentation | 2020-03-02 [Poster Presentation] High-precision modeling of distortion stomp box by deep learning using spectral features Kento Yoshimoto, Daichi Kitahara, Akira Hirabayashi, |
|---|---|
| PDF Download Page |  PDF download Page Link |
| Abstract(in Japanese) | (See Japanese page) |
| Abstract(in English) | We propose a method for modeling distortion stomp box with high accuracy using a deep neural network, WaveNet. The conventional method using the WaveNet adopted the error-to-signal ratio (ESR) defined in time domain as the loss function. Then, the high-frequency components were not sufficiently reproduced. To reproduce more accurate high-frequency components, we modify the loss function by adding the error of the spectral feature. We use a short-time Fourier transform and a mel frequency spectrogram as the spectral feature. Numerical experiments using an Ibanez SD9 show that the proposed method can generate modeling sounds with more accurate high-frequency components. |
| Keyword(in Japanese) | (See Japanese page) |
| Keyword(in English) | Distortion stomp box / black-box modeling / WaveNet / loss function / spectral features |
| Paper # | EA2019-124,SIP2019-126,SP2019-73 |
| Date of Issue | 2020-02-24 (EA, SIP, SP) |
| Conference Information | |
| Committee | SP / EA / SIP |
|---|---|
| Conference Date | 2020/3/2(2days) |
| Place (in Japanese) | (See Japanese page) |
| Place (in English) | Okinawa Industry Support Center |
| Topics (in Japanese) | (See Japanese page) |
| Topics (in English) | |
| Chair | Hisashi Kawai(NICT) / Kenichi Furuya(Oita Univ.) / Naoyuki Aikawa(TUS) |
| Vice Chair | Akinobu Ri(Nagoya Inst. of Tech.) / Suehiro Shimauchi(Kanazawa Inst. of Tech.) / Shigeto Takeoka(Shizuoka Inst. of Science and Tech.) / Kazunori Hayashi(Osaka City Univ) / Yukihiro Bandou(NTT) |
| Secretary | Akinobu Ri(Kyoto Univ.) / Suehiro Shimauchi(Waseda Univ.) / Shigeto Takeoka(NHK) / Kazunori Hayashi(Univ. of Tokyo) / Yukihiro Bandou(Hiroshima Univ.) |
| Assistant | Tomoki Koriyama(Univ. of Tokyo) / Yusuke Ijima(NTT) / Keisuke Imoto(Ritsumeikan Univ.) / Daisuke Morikawa(Toyama Pref Univ.) / Kenjiro Sugimoto(Waseda Univ.) |
| Paper Information | |
| Registration To | Technical Committee on Speech / Technical Committee on Engineering Acoustics / Technical Committee on Signal Processing |
|---|---|
| Language | JPN |
| Title (in Japanese) | (See Japanese page) |
| Sub Title (in Japanese) | (See Japanese page) |
| Title (in English) | [Poster Presentation] High-precision modeling of distortion stomp box by deep learning using spectral features |
| Sub Title (in English) | |
| Keyword(1) | Distortion stomp box |
| Keyword(2) | black-box modeling |
| Keyword(3) | WaveNet |
| Keyword(4) | loss function |
| Keyword(5) | spectral features |
| 1st Author's Name | Kento Yoshimoto |
| 1st Author's Affiliation | Ritsumeikan University(Ritsumeikan Univ.) |
| 2nd Author's Name | Daichi Kitahara |
| 2nd Author's Affiliation | Ritsumeikan University(Ritsumeikan Univ.) |
| 3rd Author's Name | Akira Hirabayashi |
| 3rd Author's Affiliation | Ritsumeikan University(Ritsumeikan Univ.) |
| Date | 2020-03-02 |
| Paper # | EA2019-124,SIP2019-126,SP2019-73 |
| Volume (vol) | vol.119 |
| Number (no) | EA-439,SIP-440,SP-441 |
| Page | pp.pp.135-140(EA), pp.135-140(SIP), pp.135-140(SP), |
| #Pages | 6 |
| Date of Issue | 2020-02-24 (EA, SIP, SP) |