Window Function-less DFT with Reduced Noise and Latency for Real-Time Music Analysis
Abstract
Music analysis applications demand algorithms that can provide both high time and frequency resolution while minimizing noise in an already-noisy signal. Real-time analysis additionally demands low latency and low computational requirements. We propose a DFT-based algorithm that accomplishes all these requirements by extending a method that post-processes DFT output without the use of window functions. Our approach yields greatly reduced sidelobes and noise, and improves time resolution without sacrificing frequency resolution. We use exponentially spaced output bins which directly map to notes in music. The resulting improved performance, compared to existing FFT and DFT-based approaches, creates possibilities for improved real-time visualizations, and contributes to improved analysis quality in other applications such as automatic transcription.
Cite
@article{arxiv.2410.07982,
title = {Window Function-less DFT with Reduced Noise and Latency for Real-Time Music Analysis},
author = {Cai Biesinger and Hiromitsu Awano and Masanori Hashimoto},
journal= {arXiv preprint arXiv:2410.07982},
year = {2025}
}
Comments
5 pages, 4 figures, Final version accepted to EUSIPCO 2025. TeX-generated PDF exemption due to formatting problems on arXiv. This version: clarified text throughout, replaced final figure with better representative one, added bin index k to several equations