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Algorithm for determining the endpoints of isolated utterances

Authors: L. R. Rabiner; M. R. Sambur;

Algorithm for determining the endpoints of isolated utterances

Abstract

An important problem in speech processing is to detect the presence of speech in a background of noise. This problem is often referred to as the endpoint location problem. By accurately detecting the beginning and end of an utterance, the amount of processing of the speech data can be kept to a minimum. The algorithm proposed for locating the endpoints of an utterance is based on two measures of the signal, namely, zero crossing rate and energy. The algorithm is inherently capable of performing correctly in any reasonable acoustic environment where the signal-to-noise ratio is on the order of 30 Db or better. The algorithm has been tested over a variety of recording conditions and for a large number of speakers and has been found to perform reasonably well across all tested conditions.

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    415
    popularity
    This indicator reflects the "current" impact/attention (the "hype") of an article in the research community at large, based on the underlying citation network.
    Top 1%
    influence
    This indicator reflects the overall/total impact of an article in the research community at large, based on the underlying citation network (diachronically).
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    impulse
    This indicator reflects the initial momentum of an article directly after its publication, based on the underlying citation network.
    Top 10%
Powered by OpenAIRE graph
Found an issue? Give us feedback
selected citations
These citations are derived from selected sources.
This is an alternative to the "Influence" indicator, which also reflects the overall/total impact of an article in the research community at large, based on the underlying citation network (diachronically).
BIP!Citations provided by BIP!
popularity
This indicator reflects the "current" impact/attention (the "hype") of an article in the research community at large, based on the underlying citation network.
BIP!Popularity provided by BIP!
influence
This indicator reflects the overall/total impact of an article in the research community at large, based on the underlying citation network (diachronically).
BIP!Influence provided by BIP!
impulse
This indicator reflects the initial momentum of an article directly after its publication, based on the underlying citation network.
BIP!Impulse provided by BIP!
415
Top 1%
Top 0.1%
Top 10%
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