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A Tutorial on Hidden Markov Models and Selected Applications
  • L. Rabiner
  • Mathematics, Computer Science
  • 1 February 1989
The fabric comprises a novel type of netting which will have particular utility in screening out mosquitoes and like insects and pests. The fabric is defined of voids having depth as well as widthExpand
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Fundamentals of speech recognition
1. Fundamentals of Speech Recognition. 2. The Speech Signal: Production, Perception, and Acoustic-Phonetic Characterization. 3. Signal Processing and Analysis Methods for Speech Recognition. 4.Expand
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An introduction to hidden Markov models
The basic theory of Markov chains has been known to mathematicians and engineers for close to 80 years, but it is only in the past decade that it has been applied explicitly to problems in speechExpand
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Hidden Markov Models for Speech Recognition
The use of hidden Markov models for speech recognition has become predominant in the last several years, as evidenced by the number of published papers and talks at major speech conferences. TheExpand
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Digital signal processing of speech signals
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An introduction to the application of the theory of probabilistic functions of a Markov process to automatic speech recognition
In this paper we present several of the salient theoretical and practical issues associated with modeling a speech signal as a probabilistic function of a (hidden) Markov chain. First we give aExpand
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A comparative study of several dynamic time-warping algorithms for connected-word recognition
Several different algorithms have been proposed for time registering a test pattern and a concatenated (isolated word) sequence of reference patterns for automatic connected-word recognition. TheseExpand
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A comparative performance study of several pitch detection algorithms
A comparative performance study of seven pitch detection algorithms was conducted. A speech data base, consisting of eight utterances spoken by three males, three females, and one child wasExpand
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On the use of autocorrelation analysis for pitch detection
One of the most time honored methods of detecting pitch is to use some type of autocorrelation analysis on speech which has been appropriately preprocessed. The goal of the speech preprocessing inExpand
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The segmental K-means algorithm for estimating parameters of hidden Markov models
  • B. Juang, L. Rabiner
  • Computer Science
  • IEEE Trans. Acoust. Speech Signal Process.
  • 1 September 1990
The authors discuss and document a parameter estimation algorithm for data sequence modeling involving hidden Markov models. The algorithm, called the segmental K-means method, uses theExpand
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