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Cited by 490

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Average magnitude difference function pitch extractor

Ross, M., Shaffer, H., Cohen, A., Freudberg, R., Manley, H.·1974·IEEE Transactions on Acoustics, Speech, and Signal Processing

Abstract

This paper describes a method for using the average magnitude difference function (AMDF) and associated decision logic to estimate the pitch period of voiced speech sounds. The AMDF is a variation on autocorrelation analysis where, instead of correlating the input speech at various delays (where multiplications and summations are formed at each value of delay), a difference signal is formed between the delayed speech and the original and, at each delay, the absolute magnitude of the difference is taken. The difference signal is always zero at delay = π, and exhibits deep nulls at delays corresponding to the pitch period of voiced sounds. Some of the reasons the AMDF is attractive include the following. 1) It is a simple measurement which gives a good estimate of pitch contour, 2) it has no multiply operations, 3) its dynamic range characteristics are suitable for implementation on a 16-bit machine, and 4) the nature of its operations makes it suitable for implementation on a programmable processor or in special purpose hardware. The implementation of the AMDF pitch extractor (nonreal-time simulation and real-time) is described and experimental results presented to illustrate its basic measurement properties.

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Metadata

Authors
Ross, M., Shaffer, H., Cohen, A., Freudberg, R., & Manley, H.
Venue
IEEE Transactions on Acoustics, Speech, and Signal Processing
Published
1974-10
Volume
22
Issue
5
Pages
353-362
ISSN
0096-3518 (ISSN-L)
OpenAlex
W2171321863
Cited by
490
References
1
FWCI
7.54
Type
journal article
Language
en
Open access
closed

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CoChat. (2026). Citation check: Average magnitude difference function pitch extractor. https://app.cochat.ai/papers/10.1109/tassp.1974.1162598
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Ross, M., Shaffer, H., Cohen, A., Freudberg, R., & Manley, H. (1974). Average magnitude difference function pitch extractor. IEEE Transactions on Acoustics, Speech, and Signal Processing. https://doi.org/10.1109/tassp.1974.1162598

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