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Precise automatic music transcription requires accurate modeling and identification of the spectral content of the audio signal. Whereas a deterministic model in terms of modulated periodic signals allows to distinguish different notes, the presence of multiple notes separated by octaves poses a big problem since they share the same periodicity, and hence completely overlapping spectral content. In...
Formant frequency is a one of the most important speech feature, which has widespread applications in speech recognition, synthesis, and compression. In this paper, a new time-frequency domain scheme for the estimation of formant frequencies from noise-corrupted speech signals is presented. In order to overcome the adverse effect of noise, instead of conventional autocorrelation function (ACF), a...
A new scheme for the estimation of formant frequencies from noise-corrupted speech signals is presented in this paper. In order to overcome the effect of noise, first, instead of conventional autocorrelation function (ACF), a once-repeated ACF of the observed data is employed. A ramp cosine cepstrum model of the ORACF of speech signal is developed, followed by a model-fitting based least-square optimization...
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