 | Audio and Speech Processing with MATLAB Subjects: Computer Science; Engineering & Technology; Systems & Computer Architecture; Electrical & Electronic Engineering; Networks; Digital Signal Processing; Communications & Information Processing; 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.Dr Paul Hill received his B.Sc degree from the Open University (1996), an M.Sc degree from the University of Bristol, Bristol, U.K. (1998) and a Ph.D. also from the University of Bristol (2002). His research interests include image and video analysis, compression, fusion and multiscale transforms together with audio applications such as compression, retrieval and signal separation. He is currently a senior research fellow at the Department of Electrical and Electronic Engineering at the University of Bristol. He has taught the speech and audio processing course that the university for over 8 years and has supervised numerous audio MSc projects over that time. He has published over 30 academic papers and is also an amateur musician and composer often reflecting his passion for electronic music in his lectures and presentations. |
