Audio Signal Processing and Coding (eBook)

ANDREAS SPANIAS, PhD, is Professor in Electrical Engineering at Arizona State University (ASU). He has led the development of the award-winning online software Java-DSP. His research interests include adaptive filters, speech/audio processing, multimedia, and sensor arrays. He is an IEEE Fellow and co-recipient of the IEEE Donald Fink Prize Paper Award for his work on audio coding. He was recognized by Intel Corporation for his contributions to the 60172 architecture. He is currently Associate Director of the ASU AME program and Co-Director of the ASU SenSIP Center. TED PAINTER, PhD, obtained his doctorate at ASU in 2000. He is a multimedia software architect in the Mobility and Wireless Group at Intel Corporation. His work focuses on architectural analysis, high-performance multimedia software design for mobile handsets, and definition of industry standards. He is editor of the Khronos OpenMAX DL specification. His research interests include psychoacoustics and speech and audio processing. He is co-recipient of the IEEE Donald Fink Prize Paper Award for his work on perceptual coding of digital audio. VENKATRAMAN ATTI, PhD, obtained his doctorate at ASU in 2006. He currently works as a senior engineer at Acoustic Technologies, Inc. While at ASU, he contributed to speech and audio coding, and to the Java-DSP package. His work in integrating perceptual criteria in linear predictive coding was nominated for an award at IEEE ICASSP-2005. At Acoustics Technologies, his work focuses on research and development of acoustic echo cancellation and noise reduction algorithms.

Preface.

1. Introduction.

2. Signal Processing Essentials.

3. Quantization and Entropy Coding.

4. Linear Prediction in Narrowband and Wideband Coding.

5. Psychoacoustic Principles.

6. Time-Frequency Analysis: Filter Banks and Transforms.

7. Transform Coders.

8. Subband Coders.

9. Sinusoidal Coders.

10. Audio Coding Standards and Algorithms.

11. Lossless Audio Coding and Digital Watermarking.

12. Quality Measures for Perceptual Audio Coding.

References.

Index.