Stochastic Onset Detection: an approach to detecting percussive attacks in complex audio

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Author(s)
Gifford, Toby
Brown, Andrew R.
Griffith University Author(s)
Year published
2008
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This paper introduces a new onset detection algorithm for the extraction of percussive attack times from a musical audio signal. The crux of the technique is to search for patterns of increasing noise in the signal. We therefore refer to it as the Stochastic Onset Detection (SOD) technique. This technique is designed for use with complex audio signals consisting of both pitched and percussive instrumental sounds together, and aims to report solely on the timing of percussive attacks. In contrast to most onset detection algorithms it operates in the time domain and is very efficient; suiting our requirements for ...
View more >This paper introduces a new onset detection algorithm for the extraction of percussive attack times from a musical audio signal. The crux of the technique is to search for patterns of increasing noise in the signal. We therefore refer to it as the Stochastic Onset Detection (SOD) technique. This technique is designed for use with complex audio signals consisting of both pitched and percussive instrumental sounds together, and aims to report solely on the timing of percussive attacks. In contrast to most onset detection algorithms it operates in the time domain and is very efficient; suiting our requirements for real-time detection. In this paper we describe our approach to onset detection, compare this with other approaches, outline our detection algorithm and provide preliminary results from musical trials to validate the algorithm's effectiveness.
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View more >This paper introduces a new onset detection algorithm for the extraction of percussive attack times from a musical audio signal. The crux of the technique is to search for patterns of increasing noise in the signal. We therefore refer to it as the Stochastic Onset Detection (SOD) technique. This technique is designed for use with complex audio signals consisting of both pitched and percussive instrumental sounds together, and aims to report solely on the timing of percussive attacks. In contrast to most onset detection algorithms it operates in the time domain and is very efficient; suiting our requirements for real-time detection. In this paper we describe our approach to onset detection, compare this with other approaches, outline our detection algorithm and provide preliminary results from musical trials to validate the algorithm's effectiveness.
View less >
Conference Title
Sound : Space - The Australasian Computer Music Conference 2008
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Copyright Statement
© The Author(s) 2008. The attached file is reproduced here in accordance with the copyright policy of the publisher. For information about this conference please refer to the conference's website or contact the authors.
Subject
Performing Arts and Creative Writing not elsewhere classified