Books > Computing & IT > Applications of computing > Audio processing > Speech recognition & synthesis
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Audio and Speech Processing with MATLAB (Paperback)
Loot Price: R1,624
Discovery Miles 16 240
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Audio and Speech Processing with MATLAB (Paperback)
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Speech and audio processing has undergone a revolution in preceding
decades that has accelerated in the last few years generating
game-changing technologies such as truly successful speech
recognition systems; a goal that had remained out of reach until
very recently. This book gives the reader a comprehensive overview
of such contemporary speech and audio processing techniques with an
emphasis on practical implementations and illustrations using
MATLAB code. Core concepts are firstly covered giving an
introduction to the physics of audio and vibration together with
their representations using complex numbers, Z transforms and
frequency analysis transforms such as the FFT. Later chapters give
a description of the human auditory system and the fundamentals of
psychoacoustics. Insights, results, and analyses given in these
chapters are subsequently used as the basis of understanding of the
middle section of the book covering: wideband audio compression
(MP3 audio etc.), speech recognition and speech coding. The final
chapter covers musical synthesis and applications describing
methods such as (and giving MATLAB examples of) AM, FM and ring
modulation techniques. This chapter gives a final example of the
use of time-frequency modification to implement a so-called phase
vocoder for time stretching (in MATLAB). Features A comprehensive
overview of contemporary speech and audio processing techniques
from perceptual and physical acoustic models to a thorough
background in relevant digital signal processing techniques
together with an exploration of speech and audio applications. A
carefully paced progression of complexity of the described methods;
building, in many cases, from first principles. Speech and wideband
audio coding together with a description of associated standardised
codecs (e.g. MP3, AAC and GSM). Speech recognition: Feature
extraction (e.g. MFCC features), Hidden Markov Models (HMMs) and
deep learning techniques such as Long Short-Time Memory (LSTM)
methods. Book and computer-based problems at the end of each
chapter. Contains numerous real-world examples backed up by many
MATLAB functions and code.
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