Glottal Inverse Filtering of Speech Based on Homomorphic Prediction: A Cepstrum-Based Algorithm Not Requiring Prior Detection of Either Pitch or Glottal Closure

Abstract

Pathological voices have features that make them distinct from normophonic voices. In fact, the unstability of phonation associated to some voice disorders has a big impact on the spectral envelope of the speech signal and also on the feasibility of reliable pitch detection. These two issues (characteristics of the spectral envelope and pitch detection) and corresponding assumptions play a key role in many current inverse filtering algorithms. Thus, the inverse filtering of disordered or special voices is not a solved problem yet. Nevertheless, the assessment of glottal function is expected to be useful in voice function evaluation. This paper approaches the problem of inverse filtering by homomorphic prediction. While not favoured much by researchers in recent literature, such an approach offers two potential advantages: it does not require previous pitch detection and it does not rely on any assumptions about the spectral enevelope of the glottal signal. Its performance is herein assessed and compared to that of an adaptive inverse filtering method making use of synthetic voices produced with a biomechanical voice production model. Results indicate that the performance of the inverse filtering based on homomorphic prediction is within the range of that of adaptive inverse filtering and, at the same time, it has a better behaviour when the spectral envelope of the glottal signal does not suit an all-pole model of predefined order.