Frequency-domain maximum likelihood pitch determination approach

The rate of oscillation of the vocal cords known as the pitch is an important sound feature that is useful in many speech applications. A novel approach for the automatic detection and estimation of the rate of oscillation of the vocal cords is described. The importance of this approach stems from the fact that pitch determination is conducted using three independent stages: a segmentation stage; a voiced-unvoiced classification stage; and a pitch estimation stage. Segmentation and the detection of voiced segments are implemented prior to pitch estimation in order to: exclude unvoiced sounds and silence from biasing the result of pitch estimation; employ a simple segmentation procedure with low computational complexity and time-delay; enhance the accuracy of voiced-unvoiced classification by including additional features in voicing detection; help pitch tracking by testing similarities over successive segments and to make use of a different analysis domain that enables a high resolution pitch estimation. A frequency-domain maximum likelihood procedure is used for the estimation of the pitch frequency of voiced segments by maximizing a log-likelihood function over the range of possible pitch frequencies in conversational speech. An efficient simplified realization of the generalized likelihood ratio segmentation method is also presented. Computer simulations on a number of utterances show that this approach gives an accurate, reliable and robust estimation of the pitch of voiced sounds.