Inverse filtering in singing voice: a critical analysis

Abstract

Inverse filtering provides a noninvasive method to extract the voice source, and thus get insight into voice quality. Although this technique is widely used in speech analysis, this is not the case in singing voice, where its use has been even questioned by some authors. In this paper, a comparative study of some representative inverse filtering techniques will be presented in order to identify their main limitations in singing voice analysis. After a rough classification of the inverse filtering techniques, three representative procedures will be selected in order to cover all kind of approaches, and then evaluated taking into account two relevant features: their fundamental frequency limitation, and their sensitivity to the source-tract interaction. To make this comparative study possible, an interactive source-filter model we propose will be used such that the source-tract interaction can be controlled. In this way, the above-mentioned effects will be evaluated based on a simulation analysis, with a realistic singing production model. Natural singing voice results will be also reported to validate the simulations. This study will allow concluding that the main limiting aspect of inverse filtering in singing voice analysis is the fundamental frequency limitation, whereas the source-tract interaction represents a less relevant issue