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HTK is a toolkit for building Hidden Markov Models (HMMs). HMMs can be used to model any
time series and the core of HTK is similarly general-purpose. However, HTK is primarily designed
for building HMM-based speech processing tools, in particular recognisers. Thus, much of the
infrastructure support in HTK is dedicated to this task. As shown in the picture alongside, there
are two major processing stages involved. Firstly, the HTK training tools are used to estimate
the parameters of a set of HMMs using training utterances and their associated transcriptions.
Secondly, unknown utterances are transcribed using the HTK recognition tools.
The main body of this book is mostly concerned with the mechanics of these two processes.
However, before launching into detail it is necessary to understand some of the basic principles of
HMMs. It is also helpful to have an overview of the toolkit and to have some appreciation of how
training and recognition in HTK is organised.
This first part of the book attempts to provide this information. In this chapter, the basic ideas
of HMMs and their use in speech recognition are introduced. The following chapter then presents a
brief overview of HTK and, for users of older versions, it highlights the main differences in version
2.0 and later. Finally in this tutorial part of the book, chapter 3 describes how a HMM-based
speech recogniser can be built using HTK. It does this by describing the construction of a simple
small vocabulary continuous speech recogniser.
The second part of the book then revisits the topics skimmed over here and discusses each in detail. This can be read in conjunction with the third and final part of the book which provides a reference manual for HTK. This includes a description of each tool, summaries of the various
parameters used to configure HTK and a list of the error messages that it generates when things go wrong.
Finally, note that this book is concerned only with HTK as a tool-kit. It does not provide information for using the HTK libraries as a programming environment.



For More Information: http://htk.eng.cam.ac.uk/

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