A Fast and Accurate Pitch Estimation Algorithm Based on the Pseudo Wigner-Ville Distribution

TL;DR

This paper introduces a novel, fast, and accurate pitch estimation algorithm leveraging the pseudo Wigner-Ville distribution's high resolution, combined with cepstrum pre-filtering, achieving state-of-the-art accuracy in speech analysis.

Contribution

The paper presents a new PWVD-based pitch estimation method with an efficient computation algorithm and cepstrum pre-filtering to reduce interference, improving accuracy and speed.

Findings

Achieves a mean absolute error of around 4Hz in pitch estimation.

Effective at voiced/unvoiced classification.

Handles sudden frequency changes well.

Abstract

Estimation of fundamental frequency (F0) in voiced segments of speech signals, also known as pitch tracking, plays a crucial role in pitch synchronous speech analysis, speech synthesis, and speech manipulation. In this paper, we capitalize on the high time and frequency resolution of the pseudo Wigner-Ville distribution (PWVD) and propose a new PWVD-based pitch estimation method. We devise an efficient algorithm to compute PWVD faster and use cepstrum-based pre-filtering to avoid cross-term interference. Evaluating our approach on a database with speech and electroglottograph (EGG) recordings yields a state-of-the-art mean absolute error (MAE) of around 4Hz. Our approach is also effective at voiced/unvoiced classification and handling sudden frequency changes.