Pitch Estimation by Denoising Preprocessor and Hybrid Estimation Model

2023/05/06 by Hung, Yu Cheng, Chen, Ping Hung, Ding, Jian Jiun
#Audio and Speech Processing (eess.AS) #FOS: Computer and information sciences #FOS: Electrical engineering #Multimedia (cs.MM) #Sound (cs.SD) #electronic engineering #information engineering

paper · doi:10.48550/arxiv.2305.03982

Abstract

Pitch estimation is to estimate the fundamental frequency and the midi number and plays a critical role in music signal analysis and vocal signal processing. In this work, we proposed a new architecture based on a learning-based enhancement preprocessor and a combination of several traditional and deep learning pitch estimation methods to achieve better pitch estimation performance in both noisy and clean scenarios. We test 17 different types of noise and 4 SNRdb noise levels. The results show that the proposed pitch estimation can perform better in both noisy and clean scenarios with short response time.

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