Theory and Application of Digital Speech Processing by L. R. ...

DRAFT: L. R. Rabiner and R. W. Schafer, June 3, 2009
26 CHAPTER 1. INTRODUCTION TO DIGITAL SPEECH PROCESSING
Figure 1.14: General view of information manipulation and processing
basic information source and the measurement or observation is generally the
acoustic waveform (although it could equally well be a set of positions of the
articulators (over time), or even measurements of the neural control signals for
the articulators.
Signal processing involves first obtaining a representation of the signal based
on a given model and then applying of some higher level transformation in order
to put the signal into a more convenient form. The last step in the process is the
extraction and utilization of the message information by either human listeners
or machines. By way of example, a system whose function is to automatically
identify a speaker from a given set of speakers might use a time-dependent
spectral representation of the speech signal. One possible signal transformation
would be to average spectra across an entire sentence, compare the average
spectrum to a stored averaged spectrum template for each possible speaker,
and then based on a spectral similarity measurement choose the identity of the
unknown speaker. For this example, the information in the signal is the identity
of the speaker.
Thus we see that processing of speech signals generally involves two tasks.
First, it is a vehicle for obtaining a general representation of a speech signal
in either waveform or parametric form. Second, signal processing serves the
function of aiding in the process of transforming the signal representation into
alternate forms which are less general in nature, but more appropriate to specific
applications. Throughout this book we will see numerous specific examples of
the importance of signal processing in the area of speech communication.