Glottal source estimation robustness: A comparison of sensitivity of voice source estimation techniques
This work addresses voice source estimation for speech processing applications, but it is incremental as it builds on and compares to existing state-of-the-art methods.
The paper tackled the problem of estimating the voice source from speech waveforms by proposing a novel Anticausality Dominated Regions (ACDR) technique, which showed significant improvement in robustness against noise and errors compared to existing methods like ZZT and IAIF, as measured by spectral distortion and glottal formant determination rate on synthetic signals.
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.