Extraction of pitch in adverse conditions

This paper proposes a method for the extraction of pitch in adverse conditions. Real environment in which the degradation is due to several unpredictable sources like, additive noise, reverberation and channel noise is treated as adverse condition in this study. The proposed method is based on the knowledge of Glottal Closure (GC) events. GC event is the instant at which closure of vocal folds takes place within a pitch period. The Hubert envelope of the Linear Prediction (LP) residual gives information about the location of GC events. Autocorrelation analysis is performed on the Hubert envelope of the LP residual. The properties of the Hubert envelope of the LP residual are exploited for the extraction of pitch from the autocorrelation sequence. The results of the proposed method are compared with the Simple Inverse Filtering Technique (SIFT) algorithm. The performance of the proposed algorithm is found to be superior, even in adverse conditions.