A novel method of formant analysis and glottal inverse filtering

Abstract

This paper presents a class of methods for automatically extracting formant parameters from speech. The methods rely on an iterative optimization algorithm. It was found that formant parameter data derived with these methods was less prone to discontinuity errors than conventional methods. Also, experiments were conducted that demonstrated that these methods are capable of better accuracy in formant estimation than LPC, especially for the first formant. In some cases, the analytic (non-iterative) solution has been derived, making real time applications feasible. The main target that we have been pursuing is text-to-speech (TTS) conversion. These methods are being used to automatically analyze a concatenation database, without the need for a tuning phase to fix errors. In addition, they are instrumental in realizing high quality pitch tracking, and pitch epoch marking.