Please use this identifier to cite or link to this item: http://localhost:8080/xmlui/handle/123456789/3131
Title: Efficient pitch detection algorithms for pitched musical instrument sounds: A comparative performance evaluation
Authors: Singh, Chetan Pratap
Kumar, T Kishore
Keywords: Autocorrelation
AMDF
Issue Date: 2014
Publisher: Proceedings of the 2014 International Conference on Advances in Computing, Communications and Informatics, ICACCI 2014
Citation: 10.1109/ICACCI.2014.6968303
Abstract: Pitch detection of an audio signal is an interesting research topic in the field of speech signal processing. Pitch is one of the most important perceptual features, as it conveys much information about the audio signal. It is closely related to the physical feature of fundamental frequency fo. For musical instrument sounds, the fo and the measured pitch can be considered equivalent. In this paper four pitch detection algorithms have been proposed for pitched musical instrument sounds. The goal of this paper is to investigate how these algorithms should be adapted to pitched musical instrument sounds analysis and to provide a comparative performance evaluation of the most representative state-of-the-art approaches. This study is carried out on a large database of pitched musical instrument sounds, comprising four types of pitched musical instruments violin, trumpet, guitar and flute. The algorithmic performance is assessed according to the ability to estimate pitch contour accurately.
Description: NITW
URI: http://localhost:8080/xmlui/handle/123456789/3131
Appears in Collections:Electronics and Communication Engineering



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