Datasets & Competitions
Speech detection systems are known as a type of audio classifier systems which are used to recognize, detect or mark parts of audio signal including human speech. Here, a novel robust feature named Long-Term Spectral Pseudo-Entropy (LTSPE) is proposed to detect speech and its purpose is to improve performance in combination with other features, increase accuracy and to have acceptable performance. Experimental results show that if LTSPE is combined with other features, performance of the detector is improved.
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In order to discriminate and mark audio signal segments which include normal human speech and discriminate segments which do not include speech (like silence, music and noise), Speech/Music Discrimination (SMD) systems are used. Using this definition, SMD systems can be considered as a specific or accurate type of speech activity detection system.
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The metaheuristic optimization algorithms are relatively the new kinds of optimization algorithms which are widely used for difficult optimization problems in which the classic methods cannot be applied and are considered as known and very broad methods for crucial optimization problems. Here, a new metaheuristic optimization algorithm is presented for which the main idea is extracted from a kind of motion in physics and is expected to have better results compared to other optimization algorithms in this field to present a novel method for achieving a more desirable point.
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630 Views