Digital Image Processing
Linear Prediction of Speech
Systematic errors in the formant analysis of steady-state vowels
Speech Communication
Discrete-time speech signal processing: principles and practice
Discrete-time speech signal processing: principles and practice
A nonparametric test for stationarity based on local Fourier analysis
ICASSP '09 Proceedings of the 2009 IEEE International Conference on Acoustics, Speech and Signal Processing
Filterbank reconstruction of bandlimited signals from nonuniformand generalized samples
IEEE Transactions on Signal Processing
IEEE Transactions on Audio, Speech, and Language Processing
A scale-rate filter selection method in the spectro-temporal domain for phoneme classification
Computers and Electrical Engineering
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This paper considers the problem of obtaining an accurate spectral representation of speech formant structure when the voicing source exhibits a high fundamental frequency. Our work is inspired by auditory perception and physiological studies implicating the use of pitch dynamics in speech by humans. We develop and assess signal processing schemes aimed at exploiting temporal change of pitch to address the high-pitch formant frequency estimation problem. Specifically, we propose a 2-D analysis framework using 2-D transformations of the time-frequency space. In one approach, we project changing spectral harmonics over time to a 1-D function of frequency. In a second approach, we draw upon previous work of Quatieri and Ezzat et al. [1], [2], with similarities to the auditory modeling efforts of Chi et al. [3], where localized 2-D Fourier transforms of the time-frequency space provide improved source-filter separation when pitch is changing. Our methods show quantitative improvements for synthesized vowels with stationary formant structure in comparison to traditional and homomorphic linear prediction. We also demonstrate the feasibility of applying our methods on stationary vowel regions of natural speech spoken by high-pitch females of the TIMIT corpus. Finally, we show improvements afforded by the proposed analysis framework in formant tracking on examples of stationary and time-varying formant structure.