Instantaneous Pitch Estimation via Wave-U-Net-Based Fundamental Waveform Enhancement

2026-06-12

AI Summary

This study addresses the limitations of traditional fundamental frequency extraction methods, which suffer from filtering-induced distortions in harmonic- and noise-contaminated speech, leading to insufficient accuracy in instantaneous pitch estimation. The work proposes a novel approach by formulating fundamental frequency extraction as a speech enhancement task and introduces an end-to-end framework based on Wave-U-Net to directly estimate the fundamental waveform from noisy speech. Instantaneous pitch is then derived by computing the instantaneous frequency of the estimated waveform using analytic signal theory. Evaluated across diverse scenarios—including speech, singing, musical instruments, and degraded speech—the proposed method significantly outperforms conventional deterministic approaches, achieving higher estimation accuracy and enhanced robustness.

Abstract

Instantaneous pitch estimation plays an important role in analyzing steep pitch variations such as speech prosody and singing techniques. Conventional approaches estimate instantaneous frequency after isolating the fundamental waveform from signals that contain harmonics and noise, which makes the accuracy sensitive to imperfect fundamental filtering. In this study, we formulate fundamental waveform filtering as a speech enhancement problem. Specifically, we train a Wave-U-Net model to extract a fundamental waveform from an input speech signal. The instantaneous pitch is then obtained by computing the instantaneous frequency from the analytic signal of the estimated fundamental waveform. Experimental results show that the proposed method outperforms conventional deterministic approaches and provides accurate and robust instantaneous pitch estimation across diverse domains, including speech, singing voice, musical instruments, and degraded speech signals.

Problem

• instantaneous pitch estimation
• fundamental waveform
• speech enhancement
• harmonics
• noise

Innovation

• Wave-U-Net
• instantaneous pitch estimation
• fundamental waveform enhancement
• speech enhancement
• instantaneous frequency