Part I: Prerequisites; Chapter 1: Introduction; 1.1 Why are Source Separation and Speech Enhancement Needed?; 1.2 What are the Goals of Source Separation and Speech Enhancement?; 1.3 How can Source Separation and Speech Enhancement be Addressed?; 1.4 Outline; Bibliography; Chapter 2: Time-Frequency Processing: Spectral Properties; 2.1 Time-Frequency Analysis and Synthesis; 2.2 Source Properties in the Time-Frequency Domain; 2.3 Filtering in the Time-Frequency Domain

2.4 SummaryBibliography; Chapter 3: Acoustics: Spatial Properties; 3.1 Formalization of the Mixing Process; 3.2 Microphone Recordings; 3.3 Artificial Mixtures; 3.4 Impulse Response Models; 3.5 Summary; Bibliography; Chapter 4: Multichannel Source Activity Detection, Localization, and Tracking; 4.1 Basic Notions in Multichannel Spatial Audio; 4.2 Multi-Microphone Source Activity Detection; 4.3 Source Localization; 4.4 Summary; Bibliography; Part II: Single-Channel Separation and Enhancement; Chapter 5: Spectral Masking and Filtering; 5.1 Time-Frequency Masking

5.2 Mask Estimation Given the Signal Statistics5.3 Perceptual Improvements; 5.4 Summary; Bibliography; Chapter 6: Single-Channel Speech Presence Probability Estimation and Noise Tracking; 6.1 Speech Presence Probability and its Estimation; 6.2 Noise Power Spectrum Tracking; 6.3 Evaluation Measures; 6.4 Summary; Bibliography; Chapter 7: Single-Channel Classification and Clustering Approaches; 7.1 Source Separation by Computational Auditory Scene Analysis; 7.2 Source Separation by Factorial HMMs; 7.3 Separation Based Training; 7.4 Summary; Bibliography

Chapter 8: Nonnegative Matrix Factorization8.1 NMF and Source Separation; 8.2 NMF Theory and Algorithms; 8.3 NMF Dictionary Learning Methods; 8.4 Advanced NMF Models; 8.5 Summary; Bibliography; Chapter 9: Temporal Extensions of Nonnegative Matrix Factorization; 9.1 Convolutive NMF; 9.2 Overview of Dynamical Models; 9.3 Smooth NMF; 9.4 Nonnegative State-Space Models; 9.5 Discrete Dynamical Models; 9.6 The Use of Dynamic Models in Source Separation; 9.7 Which Model to Use?; 9.8 Summary; 9.9 Standard Distributions; Bibliography; Part III: Multichannel Separation and Enhancement

Chapter 10: Spatial Filtering10.1 Fundamentals of Array Processing; 10.2 Array Topologies; 10.3 Data-Independent Beamforming; 10.4 Data-Dependent Spatial Filters: Design Criteria; 10.5 Generalized Sidelobe Canceler Implementation; 10.6 Postfilters; 10.7 Summary; Bibliography; Chapter 11: Multichannel Parameter Estimation; 11.1 Multichannel Speech Presence Probability Estimators; 11.2 Covariance Matrix Estimators Exploiting SPP; 11.3 Methods for Weakly Guided and Strongly Guided RTF Estimation; 11.4 Summary; Bibliography; Chapter 12: Multichannel Clustering and Classification Approaches