Accuracy of speaker verification via orthogonal parameters for noisy speech

An important problem in speaker verification systems arises, when the speech inputs are noise corrupted with signal to noise ratios in the range of 10 to 30 dB (noise assumed to be zero mean and white). This paper deals with the accuracy of speaker verification algorithms derived from an orthogonal parameter representation of speech. Initially, the investigations are directed to evaluate the sensitivity of orthogonal parameters to the level of noise in the speech signal. The accuracy of verification is then determined, using only those parameters that are least sensitive to additive noise. The influence of the order of the linear prediction model on verification is also studied. The verification algorithm is based on the distance measure used by Sambur. Finally thresholds are established to determine the proper choice of orthogonal parameters (used in distance computation) and the order of the linear prediction model for a given signal to noise ratio in the speech signal. The above study is then used to evaluate the accuracy of verification when speech inputs are obtained from a noisy telephone channel.