A new method for robust estimation of fundamental frequency (F0) from speech signal is proposed in this paper. The method exploits the high SNR regions of speech in time and frequency domains in the outputs of single frequency filtering (SFF) of speech signal. The high resolution in the frequency domain brings out the harmonic characteristics of speech clearly. The harmonic spacing in the high SNR regions of spectrum determine the F0. The concept of root cepstrum is used to reduce the effects of vocal tract resonances in the F0 estimation. The proposed method is evaluated for clean speech and noisy speech simulated for 15 different degradations at different noise levels. Performance of the proposed method is compared with four other standard methods of F0 extraction. From the results it is evident that the proposed method is robust for most types of degradations.

Air cavities in the tyre tread and the gap formed between tyre and pavement are excited during vehicle movement on a pavement. The former results in pipe resonance, and the latter results in horn resonance. These effects will be varying with speed of the vehicle and also because of conditions of tyre, pavement and, tyre-pavement interaction (TPI). The objective of this paper is to study the dynamic characteristics of air cavity resonances from the signals of the tyre-pavement interaction noise, which was collected by a pair of microphones, when a two wheeler is driven on a pavement at different speeds. The dynamic characteristics of the resonances are analysed using single frequency filtering (SFF) analysis of signals. The method gives spectral information at every sampling instant. The effects of impacts of the tyre treads, pavement characteristics, and TPI on the resulting cavity resonances are examined at four different vehicle speeds and for two different types of pavements. The analysis shows that the SFF spectra bring out the distinct characteristics of the pavements on the formation of air cavities and excitation of the resonances of these cavities. This analysis may help in determining the condition of the tyre and pavement.

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