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- W2023257958 abstract "In this paper we propose Fourier-Bessel cepstral coefficients (FBCC) features for robust speech recognition. The Fourier-Bessel representation of the speech signal is obtained using Bessel function as a basis set. The FBCC are extracted from zero <sup xmlns:mml=http://www.w3.org/1998/Math/MathML xmlns:xlink=http://www.w3.org/1999/xlink>th</sup> order Bessel coefficients taking into account of the perceptual characteristics of human auditory system. Recognition accuracy is measured using the CMU SPHINX-III speech recognition system using the DARPA Resource Management (RM) speech corpus for training and testing. We evaluate the FBCC in a common experimental set up and compare their performance against traditional technique such as the Mel-frequency cepstral coefficients (MFCC) for various noise conditions. The recognition accuracy is found to be better using FBCC features in comparison with MFCC features under noisy condition data." @default.
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- W2023257958 date "2012-07-01" @default.
- W2023257958 modified "2023-09-23" @default.
- W2023257958 title "Fourier-Bessel cepstral coefficients for robust speech recognition" @default.
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- W2023257958 doi "https://doi.org/10.1109/spcom.2012.6290031" @default.
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