Acoust., Speech, Signal Process., Montreal, Canada, May 2004, vol. ![]() Loizou, "Formant frequency estimation in noise," in Proc. Acoust., Speech, Signal Process., May 2002, vol. Sachs, "Robust formant tracking in noise," in Proc. Niederjohn, "Zero-crossing based spectral analysis and SVD spectral analysis for formant frequency estimation in noise," IEEE Trans. Veldhuis, "Extraction of vocal-tract system characteristics from speech signals," IEEE Trans. Quatieri, "High-pitch formant estimation by exploiting temporal change of pitch," IEEE Trans. Demirekler, "Dynamic speech spectrum representation and tracking variable number of vocal tract resonance frequencies with time-varying dirichlet process mixture models," IEEE Trans. O'Shaughnessy, Speech Communications Human and Machine, 2nd ed. Olive, "Formant tracking using context-dependent phonemic information," IEEE Trans. Milinazzo, "Formant location from LPC analysis data," IEEE Trans. Bruce, "Robust formant tracking for continuous speech with speaker variability," IEEE Trans. Ney, "Formant estimation for speech recognition," IEEE Trans. Guan, "Recognizing human emotional state from audiovisual signals," IEEE Trans. Ali, "Automatic voice disorder classification using vowel formants," in Proc. Bazzi, "Tracking vocal tract resonances using a quantized nonlinear function embedded in a temporal constraint," IEEE Trans. ![]() It is found that the proposed scheme provides better formant estimation accuracy in comparison to some of the existing methods at low levels of signal-to-noise ratio. The proposed algorithm has been tested on natural vowels as well as some naturally spoken sentences in the presence of different environmental noises. Finally, spectrum of the RACF is computed and instead of direct spectral peak picking, a model fitting scheme is introduced to find out model parameters which lead to formant estimation. Next, on each resulting band-limited noisy speech signal, a repeated autocorrelation operation is carried out, which not only reduces the effect of noise but also strengthens the dominant poles corresponding to the formant frequencies. First from given noisy speech observations, an adaptive band selection criterion is developed. It is shown that because of the repeated autocorrelation operation on band-limited signal, the proposed model can exhibit prominent formant characteristics. Considering the vocal tract as an autoregressive system, a spectral model of repeated autocorrelation function RACF of band-limited speech signal is proposed. In this paper, a noise robust formant frequency estimation scheme is developed based on a spectral model matching algorithm.
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