Abstract
Nowadays the detection of the fundamental frequency (F 0) in voice signals can be evaluated by several algorithms. There are two main attributes of these algorithms: exactness and calculation time. A considerable part of the algorithms are based on the well-known Fast Fourier Transformation (FFT). The Smoothed Spectrum Method is an FFT based process, which was developed for the F 0 detection of recorded voice signals especially the infant cry. As it will be shown the SSM provides a better accuracy than regular FFT based algorithms or the Autocorrelation Function. In case of sound recordings in noisy environment the modified SSM is able to recognize significant noise components in the recorded signal. A further advantage of SSM is that additional information of the analyzed signal can be given to improve the performance of the method.
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Várallyay, G. (2007). SSM – A Novel Method to Recognize the Fundamental Frequency in Voice Signals. In: Rueda, L., Mery, D., Kittler, J. (eds) Progress in Pattern Recognition, Image Analysis and Applications. CIARP 2007. Lecture Notes in Computer Science, vol 4756. Springer, Berlin, Heidelberg. https://doi.org/10.1007/978-3-540-76725-1_10
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DOI: https://doi.org/10.1007/978-3-540-76725-1_10
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