Time domain harmonic matching pitch estimation using time-dependent speech modeling

A new formulation of the pitch estimation problem is proposed. A speech signal is modeled as a sequence of a specified function in a time-dependent manner which allows the period and the amplitude of excitation of the signal to be time varying. The asymmetry of the signal distribution with respect to the time axis is profited from. A statistically optimized resemblance function derived from an energy criterion is obtained. The estimation of pitch period is achieved by maximizing this function. An estimation of the position and the amplitude of the maximum peak in each period for voiced speech segments is simultaneously provided. An interpretation in frequency domain shows that this approach is equivalent to the harmonic structure matching process of the recently proposed biological pitch perception. Experiments on the performances of the algorithm are presented for clean, noisy, and simulated telephone-line filtered speech, respectively. The result is extremely encouraging: the estimation is almost free from error for clean speech, no presence of the first harmonic is necessary, the estimation is of high noise immunity, and the speech model is sufficient for following rapid pitch variations. It appears that the method is at least as efficient as any existing pitch determination methods based on harmonic structure searching.