[language] Speech Recognition book

[H.M. Hubey]

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-------------------------Yet Another Book---------------------

The text concentrates on those basic statistical ideas that have proven
so fruitful
in speech recognition: hidden Markov models, data clustering, smoothing of
probability distributions, the decision tree method of equivalence
classification,
the use of information measures as goodness criteria, the maximum entropy
probability estimation. The aim is clarity, conciseness, and a unified
point of
view.
...
There are a few explicit prerequisites to understanding the book's
contents. Some
familiarity with probability, college level mathematics, and (mainly)
maturity are
required. We progress step by step, trying to be self-contained and
appealing
to common sense. No advanced theorems are invoked, not even the central
limit theorem, or the theory of matrices with nonnegative elements.

The book tries to introduce methods heuristically, sometimes delaying
mathematical
proofs, often eschewing them altogether.
                                         Frederick Jelinek
                                    Statistical Methods for Speech
Recognition
                                    MIT Press, 1997

--
M. Hubey
-o-o-o-o-o-o-o-o-o-o-o-o-o-o-o-o-o-o-o-o-o-o-o-o-o-o-o-o-o-o-o-o-o-o
The only difference between humans and machines is that humans
can be created by unskilled labor. Arthur C. Clarke

/\/\/\/\//\/\/\/\/\/\/ http://www.csam.montclair.edu/~hubey



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