TAILIEUCHUNG - DSP A Khoa học máy tính quan điểm P19

Speech Signal Processing In this chapter we treat of one of the most intricate and fascinating signals ever to be studied, human. speech. The reader has already been exposed to the basic models of speech generation and perception in Chapter 11. In this chapter we apply our knowledge of these mechanisms to the practical problem of speech modeling. Speech synthesis is the artificial generation of understandable, and (hopefully) natural-sounding speech | Digital Signal Processing A Computer Science Perspective Jonathan Y. Stein Copyright 2000 John Wiley Sons Inc. Print ISBN 0-471-29546-9 Online ISBN 0-471-20059-X 19 Speech Signal Processing In this chapter we treat of one of the most intricate and fascinating signals ever to be studied human speech. The reader has already been exposed to the basic models of speech generation and perception in Chapter 11. In this chapter we apply our knowledge of these mechanisms to the practical problem of speech modeling. Speech synthesis is the artificial generation of understandable and hopefully natural-sounding speech. If coupled with a set of rules for reading text rules that in some languages are simple but in others quite complex we get text-to-speech conversion. We introduce the reader to speech modeling by means of a naive but functional speech synthesis system. Speech recognition also called speech-to-text conversion seems at first to be a pattern recognition problem but closer examination proves understanding speech to be much more complex due to time warping effects. Although a difficult task the allure of a machine that converses with humans via natural speech is so great that much research has been and is still being devoted to this subject. There are also many other applications speaker verification emotional content extraction voice polygraph blind voice separation cocktail party effect speech enhancement and language identification to name just a few. While the list of applications is endless many of the basic principles tend to be the same. We will focus on the deriving of features . sets of parameters that are believed to contain the information needed for the various tasks. Simplistic sampling and digitizing of speech requires a high information rate in bits per second meaning wide bandwidth and large storage requirements. More sophisticated methods have been developed that require a significantly lower information rate but introduce a tolerable amount of .

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