ASSDSPFeb 1, 2019

Multi-layered Cepstrum for Instantaneous Frequency Estimation

arXiv:1902.00539v11 citations
AI Analysis

This addresses the challenge of accurate frequency estimation in noisy audio signals for applications like music analysis, but it appears incremental as it builds on existing cepstrum techniques.

The paper tackled the problem of estimating multiple fundamental frequencies in signals contaminated by high-pass filter noise, proposing the multi-layered cepstrum method, which showed potential in evaluations on a real-world polyphonic music dataset under normal and low-fidelity conditions.

We propose the multi-layered cepstrum (MLC) method to estimate multiple fundamental frequencies (MF0) of a signal under challenging contamination such as high-pass filter noise. Taking the operation of cepstrum (i.e., Fourier transform, filtering, and nonlinear activation) recursively, MLC is shown as an efficient method to enhance MF0 saliency in a step-by-step manner. Evaluation on a real-world polyphonic music dataset under both normal and low-fidelity conditions demonstrates the potential of MLC.

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