Singing Voice Detection Based on Convolutional Neural Networks

被引：0
|
作者：
Huang, Hong-Ming [1 ]
Chen, Woei-Kae [2 ]
Liu, Chien-Hung [2 ]
You, Shingchern D. [2 ]
机构：
[1] Synology Inc, Taipei, Taiwan
[2] Natl Taipei Univ Technol, Dept Comp Sci & Info Engn, Taipei, Taiwan
来源：
2018 7TH IEEE INTERNATIONAL SYMPOSIUM ON NEXT-GENERATION ELECTRONICS (ISNE) | 2018年
关键词：
singing voice detection; DFT; MFCC; convolutional neural networks;
D O I：
暂无
中图分类号：
TM [电工技术]; TN [电子技术、通信技术];
学科分类号：
0808 ; 0809 ;
摘要：
This paper investigates various structures of convolutional neural networks (CNN) for singing voice detection. The input features are MFCC (mel-frequency cepstrum coefficients), DFT (discrete Fourier transform) coefficients, and raw PCM samples. The simulation results show that DFT coefficients yields higher detection accuracy, up to 92%.
引用
收藏
页码：223 / 226
页数：4
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