Abstract
In this paper, we present a fundamental frequency determination method dependent on the autocorrelation compression of the multi-scale product of speech signal. It is based on the multiplication of compressed copies of the original autocorrelation operated on the multi-scale product. The multi-scale product is based on realising the product of the speech wavelet transform coefficients at three successive dyadic scales. We use the quadratic spline wavelet function. We compress the autocorrelation of the multi-scale product a number of times by integer factors (downsampling). Hence, when the obtained functions are multiplied, we obtain a peak with a clear maximum corresponding to the fundamental frequency. We have evaluated our method on the Keele database. Experimental results show the effectiveness of our method presenting a good performance surpassing other algorithms. Besides, the proposed approach is robust in noisy environment.
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Ben Messaoud, M.A., Bouzid, A., Ellouze, N. (2013). An Efficient Method for Fundamental Frequency Determination of Noisy Speech. In: Drugman, T., Dutoit, T. (eds) Advances in Nonlinear Speech Processing. NOLISP 2013. Lecture Notes in Computer Science(), vol 7911. Springer, Berlin, Heidelberg. https://doi.org/10.1007/978-3-642-38847-7_5
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DOI: https://doi.org/10.1007/978-3-642-38847-7_5
Publisher Name: Springer, Berlin, Heidelberg
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