• Publications
  • Influence
A Tutorial on Hidden Markov Models and Selected Applications
  • L. Rabiner
  • Computer Science, Mathematics
  • 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
Fundamentals of speech recognition
TLDR
This book presents a meta-modelling framework for speech recognition that automates the very labor-intensive and therefore time-heavy and therefore expensive and expensive process of manually modeling speech. Expand
An introduction to hidden Markov models
TLDR
The purpose of this tutorial paper is to give an introduction to the theory of Markov models, and to illustrate how they have been applied to problems in speech recognition. Expand
Theory and Application of Digital Signal Processing
TLDR
In this well-written book, Bellman and Wing have indeed accomplished the task of introducing the simplicity of the invariant imbedding method to tackle various problems of interest to engineers, physicists, applied mathematicians, and numerical analysts. Expand
Hidden Markov Models for Speech Recognition
TLDR
The role of statistical methods in this powerful technology as applied to speech recognition is addressed and a range of theoretical and practical issues that are as yet unsolved in terms of their importance and their effect on performance for different system implementations are discussed. Expand
A unified approach to short-time Fourier analysis and synthesis
TLDR
The effects of modifications made to the short-time transform are explicitly shown on the resulting signal and it is shown that a formal duality exists between the two synthesis methods based on the properties of the window used for obtaining theshort-time Fourier transform. Expand
An introduction to the application of the theory of probabilistic functions of a Markov process to automatic speech recognition
TLDR
This paper presents several of the salient theoretical and practical issues associated with modeling a speech signal as a probabilistic function of a (hidden) Markov chain, and focuses on a particular class of Markov models, which are especially appropriate for isolated word recognition. Expand
A comparative study of several dynamic time-warping algorithms for connected-word recognition
TLDR
The theoretical differences and similarities among the various algorithms for automatic connected-word recognition are discussed and an experimental comparison shows that for typical applications, the level-building algorithm performs better than either the two-level DP matching or the sampling algorithm. Expand
A comparative performance study of several pitch detection algorithms
TLDR
A comparative performance study of seven pitch detection algorithms was conducted, consisting of eight utterances spoken by three males, three females, and one child, to assess their relative performance as a function of recording condition, and pitch range of the various speakers. Expand
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