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Extraction Of A Speech Signal In The Presence Of A Musical Note Signal (1996)
BibTeX
@MISC{And96extractionof,
author = {Chong And and K. Chong and R. Togneri},
title = {Extraction Of A Speech Signal In The Presence Of A Musical Note Signal},
year = {1996}
}
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Abstract
This paper presents the methodology of extracting a speech signal in the presence of a musical note signal using the GRNN (General Regression Neural Network). An overview of GRNN is presented first, followed by preliminary simulations. Results of extracting speech in the presence of a flute and a cello note are also presented. INTRODUCTION Speech and musical note signals have overlapping spectra. Hence, extraction of the speech signal cannot be done by using conventional filters. The new approach is to employ a type of artificial neural network (ANN) called the General Regression Neural Network (GRNN). The GRNN does not need any information from the frequency domain -- it learns to map an input signal to the desired output signal by way of examples. The methodology involves training the GRNN to map an incoming signal, which is a composite of speech and musical note signals, to the desired output signal, which is the musical note signal alone. If the mapping is done successfully, then t...
