Kumar Neeraj, Kumar Raubin
Department of Electronics Engineering, IIT(ISM), Dhanbad, Jharkhand, 826004, India.
Talentica Software (I) Pvt. Limited, Pune, India.
Heliyon. 2020 Jan 29;6(1):e03243. doi: 10.1016/j.heliyon.2020.e03243. eCollection 2020 Jan.
In this paper, a Wavelet transform-based approach for estimation of multipitch in music signal has been proposed. Among the Morlet Wavelet (MW), Mexican hat, and Shannon wavelet that belong to the widely used wavelets in different applications, the Morlet wavelet performs well for estimation of pitch in polyphonic music signals. This is why a method involving modification of the Morlet wavelet has been proposed for achieving better accuracy in estimation of multiple pitches in polyphonic music. Performance of the Modified Morlet Wavelet (MMW) based Multipitch Estimation (MPE) scheme has been compared with that of a method based on Fast Fourier Transform and another based on the original Morlet Wavelet, in terms of percentage Gross Pitch Error (GPE). Piano chord data base and Standard music IOWA data base have been used for performance evaluation of the proposed scheme. Simulation results show that percentage error in pitch (described by the fundamental frequency) is minimum for the proposed i.e. MMW-based method.
本文提出了一种基于小波变换的音乐信号多基音估计方法。在不同应用中广泛使用的小波,如莫雷小波(MW)、墨西哥帽小波和香农小波中,莫雷小波在复调音乐信号的基音估计方面表现良好。这就是为什么提出了一种涉及修改莫雷小波的方法,以在复调音乐的多基音估计中获得更高的精度。基于修正莫雷小波(MMW)的多基音估计(MPE)方案的性能,已与基于快速傅里叶变换的方法和基于原始莫雷小波的方法,在总基音误差百分比(GPE)方面进行了比较。钢琴和弦数据库和标准音乐爱荷华数据库已用于评估所提出方案的性能。仿真结果表明,对于所提出的即基于MMW的方法,基音(由基频描述)的百分比误差最小。