Evaluation of glottal closure instant detection in a range of voice qualities

Abstract

Recently developed speech technology platforms, such as statistical speech synthesis and voice transformation systems, facilitate the modification of voice characteristics. To fully exploit the potential of such platforms, speech analysis algorithms need to be able to handle the different acoustic characteristics of a variety of voice qualities. Glottal closure instant (GCI) detection is typically required in the analysis stages, and thus the importance of robust GCI algorithms is evident. The current study examines some important analysis signals relevant to GCI detection, for a range of phonation types. Furthermore, a new algorithm is proposed which builds on an existing GCI algorithm to optimise the performance when analysing speech involving different phonation types. Results suggest improvements in the GCI detection rate for creaky voice due to a reduction in false positives. When there is a lack of prominent peaks in the Linear Prediction residual, as found for breathy and harsh voice, the results further indicate some enhancement of GCI identification accuracy for the proposed method.