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

页码：223 / 226

页数：4

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