Pitch estimation and voicing detection based on a sinusoidal speech model

A technique for estimating the pitch of a speech waveform is developed. It fits a harmonic set of sine waves to the input data using a mean-squared-error (MSE) criterion. By exploiting a sinusoidal model for the input speech waveform, a pitch estimation criterion is derived that is inherently unambiguous, uses pitch-adaptive resolution, uses small-signal suppression to provide enhanced discrimination, and uses amplitude compression to eliminate the effects of pitch-formant interaction. The normalized minimum mean squared error proves to be a powerful discriminant for estimating the likelihood that a given frame of speech is voiced