Audio and Speech Processing with MATLAB

Explore Financial institution For Sound and Speech Handling using MATLAB

1. ISBN-10

   1498762743
2. ISBN-13

   978-1498762748Speech and audio processing has experienced a revolution in the past years that has sped up in the last few years creating game-changing technologies such as highly successful speech recognition systems; an objective that had remained out of reach until very recently. This book presents the reader a thorough overview of such cutting-edge speech and audio processing techniques with an emphasis on practical implementations and illustrations using MATLAB code. Fundamental principles are initially 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 provide an overview of the human auditory system and the basics of psychoacoustics. Insights, results, and analyses given in these chapters are subsequently used as the basis of understanding of the core part of the book covering: wideband audio compression (MP3 audio etc.), speech recognition and speech coding.

   The final chapter covers musical synthesis and applications describing techniques such as (and providing MATLAB examples of) AM, FM and ring modulation techniques. This chapter offers a final example of using time-frequency modification to implement a so-called phase vocoder for time stretching (in MATLAB).

   Benefits

    

   • A thorough overview of modern speech and audio processing techniques from perceptual and physical acoustic models to a comprehensive 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 techniques; building, in many cases, from first principles.

    

   • Speech and wideband audio coding together with an overview of relevant standardized formats (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-Term Memory (LSTM) methods.

    

   • Manual and computer-based exercises at the end of each chapter.

    

   • Contains numerous real-world examples backed up by many MATLAB functions and code.