Quasi closed phase analysis of speech signals using time varying weighted linear prediction for accurate formant tracking

Abstract

Recent research on temporally weighted linear prediction shows that quasi closed phase (QCP) analysis of speech signals provides better modeling of the vocal tract and the glottal source. Quasi closed phase analysis gives more weightage on the closed phase of the glottal cycle, at the same time deemphasizing the region around the instant of significant excitation which is often poorly predicted. However, all the traditional analysis techniques including the QCP analysis is performed over short intervals of time. They do not impose any continuity constraints either on the vocal tract system or the glottal source. Such constraints are often imposed at a later stage to either smooth or track the estimated features over time. Time varying linear prediction (TVLP) provides a framework for modeling speech with a long-term continuity constraint imposed on the vocal tract shape. In this paper, we propose a new method for accurate modeling and tracking of the vocal tract resonances by integrating the advantages of a QCP analysis with that of TVLP. Formant tracking experiments show consistent improvement in performance over traditional LP or TVLP methods under a variety of conditions including different voice types and over a wide range of fundamental frequency.