Mads G. Christensen's Books

Introduction to Audio Processing

By: Mads G. Christensen

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Introduction to Audio Processing

By: Mads G. Christensen

This textbook presents an introduction to signal processing for audio applications. The author’s approach posits that math is at the heart of audio processing and that it should not be simplified. He thus retains math as the core of signal processing and includes concepts of difference equations, convolution, and the Fourier Transform. Each of these is presented in a context where they make sense to the student and can readily be applied to build artifacts. Each chapter in the book builds on the previous ones, building a linear, coherent story. The book starts with a definition of sound and goes on to discuss digital audio signals, filters, The Fourier Transform, audio effects, spatial effects, audio equalizers, dynamic range control, and pitch estimation. The exercises in each chapter cover the application of the concepts to audio signals. The exercises are made specifically for Pure Data (Pd) although traditional software, such as MATLAB, can be used. The book is intended for students in media technology bachelor programs. The book is based on material the author developed teaching on the topic over a number of years.

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Page Count

244

Publisher

Springer

Published Date

ISBN 10

3030117812

ISBN 13

9783030117818

Signal Enhancement with Variable Span Linear Filters

By: Jacob Benesty,Mads G. Christensen,Jesper R. Jensen

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Signal Enhancement with Variable Span Linear Filters

By: Jacob Benesty,Mads G. Christensen,Jesper R. Jensen

This book introduces readers to the novel concept of variable span speech enhancement filters, and demonstrates how it can be used for effective noise reduction in various ways. Further, the book provides the accompanying Matlab code, allowing readers to easily implement the main ideas discussed. Variable span filters combine the ideas of optimal linear filters with those of subspace methods, as they involve the joint diagonalization of the correlation matrices of the desired signal and the noise. The book shows how some well-known filter designs, e.g. the minimum distortion, maximum signal-to-noise ratio, Wiener, and tradeoff filters (including their new generalizations) can be obtained using the variable span filter framework. It then illustrates how the variable span filters can be applied in various contexts, namely in single-channel STFT-based enhancement, in multichannel enhancement in both the time and STFT domains, and, lastly, in time-domain binaural enhancement. In these contexts, the properties of these filters are analyzed in terms of their noise reduction capabilities and desired signal distortion, and the analyses are validated and further explored in simulations.

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Page Count

176

Publisher

Springer

Published Date

ISBN 10

9812877398

ISBN 13

9789812877390

Speech Enhancement

A Signal Subspace Perspective

By: Jacob Benesty,Jesper Rindom Jensen,Mads Graesboll Christensen,Jingdong Chen

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Speech Enhancement

A Signal Subspace Perspective

By: Jacob Benesty,Jesper Rindom Jensen,Mads Graesboll Christensen,Jingdong Chen

Speech enhancement is a classical problem in signal processing, yet still largely unsolved. Two of the conventional approaches for solving this problem are linear filtering, like the classical Wiener filter, and subspace methods. These approaches have traditionally been treated as different classes of methods and have been introduced in somewhat different contexts. Linear filtering methods originate in stochastic processes, while subspace methods have largely been based on developments in numerical linear algebra and matrix approximation theory. This book bridges the gap between these two classes of methods by showing how the ideas behind subspace methods can be incorporated into traditional linear filtering. In the context of subspace methods, the enhancement problem can then be seen as a classical linear filter design problem. This means that various solutions can more easily be compared and their performance bounded and assessed in terms of noise reduction and speech distortion. The book shows how various filter designs can be obtained in this framework, including the maximum SNR, Wiener, LCMV, and MVDR filters, and how these can be applied in various contexts, like in single-channel and multichannel speech enhancement, and in both the time and frequency domains. - First short book treating subspace approaches in a unified way for time and frequency domains, single-channel, multichannel, as well as binaural, speech enhancement - Bridges the gap between optimal filtering methods and subspace approaches - Includes original presentation of subspace methods from different perspectives

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Page Count

143

Publisher

Elsevier

Published Date

ISBN 10

0128002530

ISBN 13

9780128002537

Book's by Mads G. Christensen

Introduction to Audio Processing

Introduction to Audio Processing

Signal Enhancement with Variable Span Linear Filters

Signal Enhancement with Variable Span Linear Filters

Speech Enhancement

Speech Enhancement

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