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The '''Viterbi algorithm''' is a [[dynamic programming]] [[algorithm]] for obtaining the [[Maximum a posteriori estimation|maximum a posteriori probability estimate]] of the most [[likelihood function|likely]] sequence of hidden states—called the '''Viterbi path'''—that results in a sequence of observed events. This is done especially in the context of [[Markov information source]]s and [[hidden Markov model]]s (HMM).
The algorithm has found universal application in decoding the [[convolutional code]]s used in both [[CDMA]] and [[GSM]] digital cellular, [[dial-up]] modems, satellite, deep-space communications, and [[802.11]] wireless LANs. It is now also commonly used in [[speech recognition]], [[speech synthesis]], [[diarization]],<ref>Xavier Anguera et al., [http://www1.icsi.berkeley.edu/~vinyals/Files/taslp2011a.pdf "Speaker Diarization: A Review of Recent Research"] {{Webarchive|url=https://web.archive.org/web/20160512200056/http://www1.icsi.berkeley.edu/~vinyals/Files/taslp2011a.pdf |date=2016-05-12 }}, retrieved 19. August 2010, IEEE TASLP</ref> [[keyword spotting]], [[computational linguistics]], and [[bioinformatics]]. For example, in [[speech-to-text]] (speech recognition), the acoustic signal is treated as the observed sequence of events, and a string of text is considered to be the "hidden cause" of the acoustic signal. The Viterbi algorithm finds the most likely string of text given the acoustic signal.
== History ==
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