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DC-constrained linear prediction for glottal inverse filtering

Closed phase covariance (CP) analysis is a glottal inverse filtering method which estimates the vocal tract during the glottal closed phase. Since closed phase durations are typically short, the vocal tract computation with linear prediction is vulnerable to the covariance frame position. This study proposes a modified CP algorithm in which a DC-gain constraint is imposed in optimizing the linear predictive inverse model of the vocal tract. Results show that the algorithm improves the robustness of the CP analysis on the covariance frame position.