Glottal source estimation robustness: A comparison of sensitivity of voice source estimation techniques

TL;DR

This study compares the robustness of three voice source estimation techniques, introducing a novel ACDR-based method that outperforms others in noisy conditions and with GCI errors, enhancing speech decomposition reliability.

Contribution

The paper introduces a new ACDR-based approach for glottal source estimation and compares its robustness to existing methods under various noise and error conditions.

Findings

ACDR method shows improved robustness over ZZT and IAIF.

Performance degrades with noise and GCI errors, but less so for ACDR.

Fundamental frequency and formant influence estimation accuracy.

Abstract

This paper addresses the problem of estimating the voice source directly from speech waveforms. A novel principle based on Anticausality Dominated Regions (ACDR) is used to estimate the glottal open phase. This technique is compared to two other state-of-the-art well-known methods, namely the Zeros of the Z-Transform (ZZT) and the Iterative Adaptive Inverse Filtering (IAIF) algorithms. Decomposition quality is assessed on synthetic signals through two objective measures: the spectral distortion and a glottal formant determination rate. Technique robustness is tested by analyzing the influence of noise and Glottal Closure Instant (GCI) location errors. Besides impacts of the fundamental frequency and the first formant on the performance are evaluated. Our proposed approach shows significant improvement in robustness, which could be of a great interest when decomposing real speech.