Robust pitch tracking in the car environment

In this paper we compare four different pitch tracking algorithms - autocorrelation, cepstrum, harmonic product spectrum, and a new method based on the modulation spectrum - and investigate their fitness for noisy environments. From each tracker, possible ƒ0 candidates in every time window are stored over a 10-frame interval, and the best contour is computed through a Viterbi search. The audio data comprises speech samples recorded in a moving car with a microphone setup commonly used for car speech applications like speakerphones. To see how performances deteriorate with increasing noise level, a second audio test set is prepared by blending clean speech recordings and noise at different signal-ta-noise ratios.