Speech enhancement : theory and practice /: theory and practice. (2013)

• Record Type: Book
• Further Information: Note: By Philipos C. Loizou.
• Other Names: Loizou, Philipos C
• Contents: Introduction; Understanding the Enemy: Noise; Classes of Speech Enhancement Algorithms; Book Organization; References; ; Part I Fundamentals ; ; Discrete-Time Signal Processing and Short-Time Fourier Analysis ; Discrete-Time Signals; Linear Time-Invariant Discrete-Time Systems; z-Transform; Discrete-Time Fourier Transform; Short-Time Fourier Transform; Spectrographic Analysis of Speech Signals; Summary; References; ; Speech Production and Perception ; Speech Signal; Speech Production Process; Engineering Model of Speech Production; Classes of Speech Sounds; Acoustic Cues in Speech Perception; Summary; References; ; Noise Compensation by Human Listeners ; Intelligibility of Speech in Multiple-Talker Conditions; Acoustic Properties of Speech Contributing to Robustness; Perceptual Strategies for Listening in Noise; Summary; References; ; Part II Algorithms ; ; Spectral-Subtractive Algorithms ; Basic Principles of Spectral Subtraction; Geometric View of Spectral Subtraction; Shortcomings of the Spectral Subtraction Method; Spectral Subtraction Using Oversubtraction; Nonlinear Spectral Subtraction; Multiband Spectral Subtraction; MMSE Spectral Subtraction Algorithm; Extended Spectral Subtraction; Spectral Subtraction Using Adaptive Gain Averaging; Selective Spectral Subtraction; Spectral Subtraction Based on Perceptual Properties; Performance of Spectral Subtraction Algorithms; Summary; References; ; Wiener Filtering ; Introduction to Wiener Filter Theory; Wiener Filters in the Time Domain; Wiener Filters in the Frequency Domain; Wiener Filters and Linear Prediction; Wiener Filters for Noise Reduction; Iterative Wiener Filtering; Imposing Constraints on Iterative Wiener Filtering; Constrained Iterative Wiener Filtering; Constrained Wiener Filtering; Estimating the Wiener Gain Function; Incorporating Psychoacoustic Constraints in Wiener Filtering; Codebook-Driven Wiener Filtering; Audible Noise Suppression Algorithm; Summary; References; ; Statistical-Model-Based Methods ; Maximum-Likelihood Estimators; Bayesian Estimators; MMSE Estimator; Improvements to the Decision-Directed Approach; Implementation and Evaluation of the MMSE Estimator; Elimination of Musical Noise; Log-MMSE Estimator; MMSE Estimation of the pth-Power Spectrum; MMSE Estimators Based on Non-Gaussian Distributions; Maximum A Posteriori (Map) Estimators; General Bayesian Estimators; Perceptually Motivated Bayesian Estimators; Incorporating Speech Absence Probability in Speech Enhancement; Methods for Estimating the A Priori Probability of Speech Absence; Summary; References; ; Subspace Algorithms ; Introduction; Using SVD for Noise Reduction: Theory; SVD-Based Algorithms: White Noise; SVD-Based Algorithms: Colored Noise; SVD-Based Methods: A Unified View; EVD-Based Methods: White Noise; EVD-Based Methods: Colored Noise; EVD-Based Methods: A Unified View; Perceptually Motivated Subspace Algorithms; Subspace-Tracking Algorithms; Summary; References; ; Noise-Estimation Algorithms ; Voice Activity Detection vs. Noise Estimation; Introduction to Noise-Estimation Algorithms; Minimal-Tracking Algorithms; Time-Recursive Averaging Algorithms for Noise Estimation; Histogram-Based Techniques; Other Noise-Estimation Algorithms; Objective Comparison of Noise-Estimation Algorithms; Summary; References; ; Part III Evaluation ; ; Evaluating Performance of Speech Enhancement Algorithms ; Quality vs. Intelligibility; Evaluating Intelligibility of Processed Speech; Evaluating Quality of Processed Speech; Evaluating Reliability of Quality Judgments: Recommended Practice; Summary; References; ; Objective Quality and Intelligibility Measures ; Objective Quality Measures; Evaluation of Objective Quality Measures; Quality Measures: Summary of Findings and Future Directions; Speech Intelligibility Measures; Evaluation of Intelligibility Measures; Intelligibility Measures: Summary of Findings and Future Directions; Summary; References; ; Comparison of Speech Enhancement Algorithms ; NOIZEUS: A Noisy Speech Corpus for Quality Evaluation of Speech Enhancement Algorithms; Comparison of Enhancement Algorithms: Speech Quality; Comparison of Enhancement Algorithms: Speech Intelligibility; Summary; References; ; Part IV Future Steps ; ; Algorithms That Can Improve Speech Intelligibility ; Reasons for the Absence of Intelligibility Improvement with Existing Noise-Reduction Algorithms; Algorithms Based on Channel Selection: A Different Paradigm for Noise Reduction; Channel-Selection Criteria; Intelligibility Evaluation of Channel-Selection-Based Algorithms: Ideal Conditions; Implementation of Channel-Selection-Based Algorithms in Realistic Conditions; Evaluating Binary Mask Estimation Algorithms; Channel Selection and Auditory Scene Analysis; Summary; References; ; Appendices ; Appendix A: Special Functions and Integrals; Appendix B: Derivation of the MMSE Estimator; Appendix C: MATLAB® Code and Speech/Noise Databases; ; Index;
• Edition: 2nd ed
• Publisher Details: Place of publication not identified : CRC Press
• Publication Date: 2013
• Extent: 1 online resource (711 pages), (207 illustrations)
• Subjects: 621.3828; Speech processing systems; Signal processing -- Digital techniques; Image processing -- Digital techniques
• Languages: English
• ISBNs: 9781466599222; 1466599227
• Access Rights: Legal Deposit; Only available on premises controlled by the deposit library and to one user at any one time; The Legal Deposit Libraries (Non-Print Works) Regulations (UK).
• Access Usage: Restricted: Printing from this resource is governed by The Legal Deposit Libraries (Non-Print Works) Regulations (UK) and UK copyright law currently in force.