Automatic estimation of formant and voice source parameters using a subspace based algorithm

An automatic method is proposed to estimate jointly formant and voice source parameters from a speech signal. A Rosenberg-Klatt model is used to approximate a voicing source waveform for voiced speech, whereas a white noise signal is assumed for the unvoiced. The vocal tract characteristic is represented by an IIR filter. The formant and anti-formant values are calculated from the IIR filter coefficients which are estimated by using the subspace-based system identification algorithm, while an exhaustive search procedure is applied to obtain the optimal source parameter values, where an error criterion is introduced in the frequency domain. An experiment has been performed to examine performance of the proposed method with natural speech. The results show that the source parameters such as open and closure instants estimated by the method is in good agreement with those defined on the electroglottograph signals and the formant values estimated are also accurate.