Open AccessDesign and Implementation of Intelligent Singer Recognition System
Author(s) -
Can Ge,
Juanjuan Li,
Lina Liu,
Gukai Li,
GuoYu Yang,
Hui Tang,
Hanlin Yang,
Yuhao Xia,
Rui Bao,
Haiyu Zhang
Publication year - 2020
Publication title -
iop conference series. materials science and engineering
Language(s) - English
Resource type - Journals
eISSN - 1757-899X
pISSN - 1757-8981
DOI - 10.1088/1757-899x/790/1/012143
Subject(s) - codebook , mel frequency cepstrum , dynamic time warping , vector quantization , speech recognition , computer science , matlab , pattern recognition (psychology) , artificial intelligence , learning vector quantization , set (abstract data type) , base (topology) , test set , pattern matching , matching (statistics) , quantization (signal processing) , computer vision , feature extraction , mathematics , mathematical analysis , statistics , programming language , operating system
An intelligent singer recognition system was designed to identify the singer. The scheme established a song library at first, then used MATLAB to extract Mel Frequency Cepstral Coefficients (MFCC) from each song in the song library, moreover, set up characteristic parameters pattern base and trained the pattern base by Vector Quantization (VQ) to obtain the final codebook base. Finally, it can correctly classify the singer based on Dynamic Time Warping (DTW) matching reference characteristic parameters pattern with test pattern. Test results showed that the system’s recognition rate is up to 90%.