Audio Source Separation and Speech Enhancement

Covers the most important techniques for both single-channel and multichannel processing. This book provides both introductory and advanced material suitable for people with basic knowledge of signal processing and machine learning.

Author: Emmanuel Vincent

Publisher: John Wiley & Sons

ISBN: 9781119279891

Category: Technology & Engineering

Page: 504

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Learn the technology behind hearing aids, Siri, and Echo Audio source separation and speech enhancement aim to extract one or more source signals of interest from an audio recording involving several sound sources. These technologies are among the most studied in audio signal processing today and bear a critical role in the success of hearing aids, hands-free phones, voice command and other noise-robust audio analysis systems, and music post-production software. Research on this topic has followed three convergent paths, starting with sensor array processing, computational auditory scene analysis, and machine learning based approaches such as independent component analysis, respectively. This book is the first one to provide a comprehensive overview by presenting the common foundations and the differences between these techniques in a unified setting. Key features: Consolidated perspective on audio source separation and speech enhancement. Both historical perspective and latest advances in the field, e.g. deep neural networks. Diverse disciplines: array processing, machine learning, and statistical signal processing. Covers the most important techniques for both single-channel and multichannel processing. This book provides both introductory and advanced material suitable for people with basic knowledge of signal processing and machine learning. Thanks to its comprehensiveness, it will help students select a promising research track, researchers leverage the acquired cross-domain knowledge to design improved techniques, and engineers and developers choose the right technology for their target application scenario. It will also be useful for practitioners from other fields (e.g., acoustics, multimedia, phonetics, and musicology) willing to exploit audio source separation or speech enhancement as pre-processing tools for their own needs.

Audio Source Separation

This book provides the first comprehensive overview of the fascinating topic of audio source separation based on non-negative matrix factorization, deep neural networks, and sparse component analysis.

Author: Shoji Makino

Publisher: Springer

ISBN: 9783319730318

Category: Technology & Engineering

Page: 385

View: 833

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This book provides the first comprehensive overview of the fascinating topic of audio source separation based on non-negative matrix factorization, deep neural networks, and sparse component analysis. The first section of the book covers single channel source separation based on non-negative matrix factorization (NMF). After an introduction to the technique, two further chapters describe separation of known sources using non-negative spectrogram factorization, and temporal NMF models. In section two, NMF methods are extended to multi-channel source separation. Section three introduces deep neural network (DNN) techniques, with chapters on multichannel and single channel separation, and a further chapter on DNN based mask estimation for monaural speech separation. In section four, sparse component analysis (SCA) is discussed, with chapters on source separation using audio directional statistics modelling, multi-microphone MMSE-based techniques and diffusion map methods. The book brings together leading researchers to provide tutorial-like and in-depth treatments on major audio source separation topics, with the objective of becoming the definitive source for a comprehensive, authoritative, and accessible treatment. This book is written for graduate students and researchers who are interested in audio source separation techniques based on NMF, DNN and SCA.

Implementation and Evaluation of Gated Recurrent Unit for Speech Separation and Speech Enhancement

This work aims to implement a single-channel speech separation and enhancement algorithm utilizing machine learning, deep neural networks (DNNs).

Author: Sagar Shah

Publisher:

ISBN: 1088327923

Category: Biomedical engineering

Page: 91

View: 349

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Hearing aids, automatic speech recognition (ASR) and many other communication systems work well when there is just one sound source with almost no echo, but their performance degrades in situations where more speakers are talking simultaneously or the reverberation is high. Speech separation and speech enhancement are core problems in the field of audio signal processing. Humans are remarkably capable of focusing their auditory attention on a single sound source within a noisy environment, by de-emphasizing all other voices and interferences in surroundings. This capability comes naturally to us humans. However, speech separation remains a significant challenge for computers. It is challenging for the following reasons: the wide variety of sound type, different mixing environment, and the unclear procedure to distinguish sources, especially for similar sounds. Also, perceiving speech in low signal/noise (SNR) conditions is hard for hearing-impaired listeners. Therefore, the motivation is to advance the speech separation algorithms to improve the intelligibility of noisy speech. Latest technologies aim to empower machines with similar abilities. Recently, the deep neural network methods achieved impressive successes in various problems, including speech enhancement, which the task to separate the clean speech of the noise mixture. Due to the advances in deep learning, speech separation can be viewed as a classification problem and treated as a supervised learning problem. Three main components of speech separation or speech enhancement using deep learning methods are acoustic features, learning machines, and training targets. This work aims to implement a single-channel speech separation and enhancement algorithm utilizing machine learning, deep neural networks (DNNs). An extensive set of speech from different speakers and noise data is collected to train a neural network model that predicts time-frequency masks from noisy and mixture speech signals. The algorithm is tested using various noises and combinations of different speakers. Its performance is evaluated in terms of speech quality and intelligibility. In this thesis, I am proposing a variant of the recurrent neural network, which is GRU (gated recurrent unit) for the speech separation and speech enhancement task. It is a simpler model than the LSTM (long short-term memory), which is used now for the task of speech enhancement and speech separation, consisting of a smaller number of parameters and matching the performance of the speech separation and speech enhancement of LSTM networks.

Independent Component Analysis for Audio and Biosignal Applications

This book brings the state-of-the-art of some of the most important current research of ICA related to Audio and Biomedical signal processing applications. The book is partly a textbook and partly a monograph.

Author: Ganesh R. Naik

Publisher: BoD – Books on Demand

ISBN: 9789535107828

Category: Medical

Page: 358

View: 273

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Independent Component Analysis (ICA) is a signal-processing method to extract independent sources given only observed data that are mixtures of the unknown sources. Recently, Blind Source Separation (BSS) by ICA has received considerable attention because of its potential signal-processing applications such as speech enhancement systems, image processing, telecommunications, medical signal processing and several data mining issues. This book brings the state-of-the-art of some of the most important current research of ICA related to Audio and Biomedical signal processing applications. The book is partly a textbook and partly a monograph. It is a textbook because it gives a detailed introduction to ICA applications. It is simultaneously a monograph because it presents several new results, concepts and further developments, which are brought together and published in the book.

Independent Component Analysis for Audio and Biosignal Applications

This book brings the state-of-the-art of some of the most important current research of ICA related to Audio and Biomedical signal processing applications. The book is partly a textbook and partly a monograph.

Author: Ganesh R. Naik

Publisher: IntechOpen

ISBN: 9535107828

Category: Medical

Page: 358

View: 901

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Independent Component Analysis (ICA) is a signal-processing method to extract independent sources given only observed data that are mixtures of the unknown sources. Recently, Blind Source Separation (BSS) by ICA has received considerable attention because of its potential signal-processing applications such as speech enhancement systems, image processing, telecommunications, medical signal processing and several data mining issues. This book brings the state-of-the-art of some of the most important current research of ICA related to Audio and Biomedical signal processing applications. The book is partly a textbook and partly a monograph. It is a textbook because it gives a detailed introduction to ICA applications. It is simultaneously a monograph because it presents several new results, concepts and further developments, which are brought together and published in the book.

Speech Enhancement

13 Frequency - Domain Blind Source Separation Hiroshi Sawada , Ryo Mukai , Shoko Araki , and Shoji Makino NTT ... Its potential audio signal applications include speech enhancement for speech recognition , teleconferences , and hearing ...

Author: Shoji Makino

Publisher: Springer Science & Business Media

ISBN: 354024039X

Category: Computers

Page: 406

View: 752

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We live in a noisy world! In all applications (telecommunications, hands-free communications, recording, human-machine interfaces, etc) that require at least one microphone, the signal of interest is usually contaminated by noise and reverberation. As a result, the microphone signal has to be "cleaned" with digital signal processing tools before it is played out, transmitted, or stored. This book is about speech enhancement. Different well-known and state-of-the-art methods for noise reduction, with one or multiple microphones, are discussed. By speech enhancement, we mean not only noise reduction but also dereverberation and separation of independent signals. These topics are also covered in this book. However, the general emphasis is on noise reduction because of the large number of applications that can benefit from this technology. The goal of this book is to provide a strong reference for researchers, engineers, and graduate students who are interested in the problem of signal and speech enhancement. To do so, we invited well-known experts to contribute chapters covering the state of the art in this focused field.

Speech and Audio Processing in Adverse Environments

Better knowledge about biological and physical interrelations c- ing along with more powerful technologies are their engines on the endless road to perfect systems. This book is an impressive image of this process.

Author: Eberhard Hänsler

Publisher: Springer Science & Business Media

ISBN: 9783540706021

Category: Technology & Engineering

Page: 736

View: 555

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Users of signal processing systems are never satis?ed with the system they currently use. They are constantly asking for higher quality, faster perf- mance, more comfort and lower prices. Researchers and developers should be appreciative for this attitude. It justi?es their constant e?ort for improved systems. Better knowledge about biological and physical interrelations c- ing along with more powerful technologies are their engines on the endless road to perfect systems. This book is an impressive image of this process. After “Acoustic Echo 1 and Noise Control” published in 2004 many new results lead to “Topics in 2 Acoustic Echo and Noise Control” edited in 2006 . Today – in 2008 – even morenew?ndingsandsystemscouldbecollectedinthisbook.Comparingthe contributions in both edited volumes progress in knowledge and technology becomesclearlyvisible:Blindmethodsandmultiinputsystemsreplace“h- ble” low complexity systems. The functionality of new systems is less and less limited by the processing power available under economic constraints. The editors have to thank all the authors for their contributions. They cooperated readily in our e?ort to unify the layout of the chapters, the ter- nology, and the symbols used. It was a pleasure to work with all of them. Furthermore, it is the editors concern to thank Christoph Baumann and the Springer Publishing Company for the encouragement and help in publi- ing this book.

Blind Speech Separation

This is the world’s first edited book on independent component analysis (ICA)-based blind source separation (BSS) of convolutive mixtures of speech.

Author: Shoji Makino

Publisher: Springer

ISBN: 9048176514

Category: Technology & Engineering

Page: 432

View: 415

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This is the world’s first edited book on independent component analysis (ICA)-based blind source separation (BSS) of convolutive mixtures of speech. This book brings together a small number of leading researchers to provide tutorial-like and in-depth treatment on major ICA-based BSS topics, with the objective of becoming the definitive source for current, comprehensive, authoritative, and yet accessible treatment.

Independent Component Analysis for Audio and Biosignal Applications

This book brings the state-of-the-art of some of the most important current research of ICA related to Audio and Biomedical signal processing applications. The book is partly a textbook and partly a monograph.

Author: Ganesh R. Naik

Publisher: IntechOpen

ISBN: 9535107828

Category: Medical

Page: 358

View: 512

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Independent Component Analysis (ICA) is a signal-processing method to extract independent sources given only observed data that are mixtures of the unknown sources. Recently, Blind Source Separation (BSS) by ICA has received considerable attention because of its potential signal-processing applications such as speech enhancement systems, image processing, telecommunications, medical signal processing and several data mining issues. This book brings the state-of-the-art of some of the most important current research of ICA related to Audio and Biomedical signal processing applications. The book is partly a textbook and partly a monograph. It is a textbook because it gives a detailed introduction to ICA applications. It is simultaneously a monograph because it presents several new results, concepts and further developments, which are brought together and published in the book.

Speech Dereverberation

Speech Dereverberation gathers together an overview, a mathematical formulation of the problem and the state-of-the-art solutions for dereverberation. Speech Dereverberation presents current approaches to the problem of reverberation.

Author: Patrick A. Naylor

Publisher: Springer Science & Business Media

ISBN: 1849960569

Category: Technology & Engineering

Page: 388

View: 562

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Speech Dereverberation gathers together an overview, a mathematical formulation of the problem and the state-of-the-art solutions for dereverberation. Speech Dereverberation presents current approaches to the problem of reverberation. It provides a review of topics in room acoustics and also describes performance measures for dereverberation. The algorithms are then explained with mathematical analysis and examples that enable the reader to see the strengths and weaknesses of the various techniques, as well as giving an understanding of the questions still to be addressed. Techniques rooted in speech enhancement are included, in addition to a treatment of multichannel blind acoustic system identification and inversion. The TRINICON framework is shown in the context of dereverberation to be a generalization of the signal processing for a range of analysis and enhancement techniques. Speech Dereverberation is suitable for students at masters and doctoral level, as well as established researchers.

Blind Source Separation

IEEE Trans. Audio Speech Lang. Proc. 19(7), 2046–2057 (2011) Ephraim, Y., Malah, D.: Speech enhancement using a minimum-mean square error shorttime spectral amplitude estimator. IEEE Trans. Acoust. Speech Signal Proc.

Author: Ganesh R. Naik

Publisher: Springer

ISBN: 9783642550164

Category: Technology & Engineering

Page: 551

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Blind Source Separation intends to report the new results of the efforts on the study of Blind Source Separation (BSS). The book collects novel research ideas and some training in BSS, independent component analysis (ICA), artificial intelligence and signal processing applications. Furthermore, the research results previously scattered in many journals and conferences worldwide are methodically edited and presented in a unified form. The book is likely to be of interest to university researchers, R&D engineers and graduate students in computer science and electronics who wish to learn the core principles, methods, algorithms and applications of BSS. Dr. Ganesh R. Naik works at University of Technology, Sydney, Australia; Dr. Wenwu Wang works at University of Surrey, UK.

Springer Handbook of Speech Processing

987–992 52.171 H. Buchner, R. Aichner, W. Kellermann: A generalization of blind source separation algorithms for convolutive mixtures based on second-order statistics, IEEE Trans. Speech Audio Process.

Author: Jacob Benesty

Publisher: Springer

ISBN: 9783540491279

Category: Technology & Engineering

Page: 1176

View: 147

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This handbook plays a fundamental role in sustainable progress in speech research and development. With an accessible format and with accompanying DVD-Rom, it targets three categories of readers: graduate students, professors and active researchers in academia, and engineers in industry who need to understand or implement some specific algorithms for their speech-related products. It is a superb source of application-oriented, authoritative and comprehensive information about these technologies, this work combines the established knowledge derived from research in such fast evolving disciplines as Signal Processing and Communications, Acoustics, Computer Science and Linguistics.

Speech Enhancement

As a result, the microphone signal has to be "cleaned" with digital signal processing tools before it is played out, transmitted, or stored. This book is about speech enhancement.

Author: Jacob Benesty

Publisher: Springer Science & Business Media

ISBN: 9783540274896

Category: Technology & Engineering

Page: 406

View: 401

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A strong reference on the problem of signal and speech enhancement, describing the newest developments in this exciting field. The general emphasis is on noise reduction, because of the large number of applications that can benefit from this technology.

Speech Processing in Modern Communication

On the other hand, the GSMM assumes in its conception that the audio signal is exclusively in one state or ... “Neural dual extended Kalman filtering: Applications in speech enhancement and monaural blind signal separation,” in Proc.

Author: Israel Cohen

Publisher: Springer Science & Business Media

ISBN: 9783642111303

Category: Technology & Engineering

Page: 342

View: 619

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Modern communication devices, such as mobile phones, teleconferencing systems, VoIP, etc., are often used in noisy and reverberant environments. Therefore, signals picked up by the microphones from telecommunication devices contain not only the desired near-end speech signal, but also interferences such as the background noise, far-end echoes produced by the loudspeaker, and reverberations of the desired source. These interferences degrade the fidelity and intelligibility of the near-end speech in human-to-human telecommunications and decrease the performance of human-to-machine interfaces (i.e., automatic speech recognition systems). The proposed book deals with the fundamental challenges of speech processing in modern communication, including speech enhancement, interference suppression, acoustic echo cancellation, relative transfer function identification, source localization, dereverberation, and beamforming in reverberant environments. Enhancement of speech signals is necessary whenever the source signal is corrupted by noise. In highly non-stationary noise environments, noise transients, and interferences may be extremely annoying. Acoustic echo cancellation is used to eliminate the acoustic coupling between the loudspeaker and the microphone of a communication device. Identification of the relative transfer function between sensors in response to a desired speech signal enables to derive a reference noise signal for suppressing directional or coherent noise sources. Source localization, dereverberation, and beamforming in reverberant environments further enable to increase the intelligibility of the near-end speech signal.

Sound Capture and Processing

This book gives a comprehensive introduction to basic acoustics and microphones, with coverage of algorithms for noise reduction, acoustic echo cancellation, dereverberation and microphone arrays; charting the progress of such technologies ...

Author: Ivan Jelev Tashev

Publisher: John Wiley & Sons

ISBN: 0470994436

Category: Technology & Engineering

Page: 388

View: 829

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Provides state-of-the-art algorithms for sound capture, processing and enhancement Sound Capture and Processing: Practical Approaches covers the digital signal processing algorithms and devices for capturing sounds, mostly human speech. It explores the devices and technologies used to capture, enhance and process sound for the needs of communication and speech recognition in modern computers and communication devices. This book gives a comprehensive introduction to basic acoustics and microphones, with coverage of algorithms for noise reduction, acoustic echo cancellation, dereverberation and microphone arrays; charting the progress of such technologies from their evolution to present day standard. Sound Capture and Processing: Practical Approaches Brings together the state-of-the-art algorithms for sound capture, processing and enhancement in one easily accessible volume Provides invaluable implementation techniques required to process algorithms for real life applications and devices Covers a number of advanced sound processing techniques, such as multichannel acoustic echo cancellation, dereverberation and source separation Generously illustrated with figures and charts to demonstrate how sound capture and audio processing systems work An accompanying website containing Matlab code to illustrate the algorithms This invaluable guide will provide audio, R&D and software engineers in the industry of building systems or computer peripherals for speech enhancement with a comprehensive overview of the technologies, devices and algorithms required for modern computers and communication devices. Graduate students studying electrical engineering and computer science, and researchers in multimedia, cell-phones, interactive systems and acousticians will also benefit from this book.

Speech and Computer

In: Interspeech 2016, pp. 352–356 (2016) Vincent, E., Virtanen, T., Gannot, S.: Audio Source Separation and Speech Enhancement, 1st edn. Wiley, Hoboken (2018) Wan, E., Nelson, A., Peterson, R.: Speech enhancement assessment resource ...

Author: Albert Ali Salah

Publisher: Springer

ISBN: 9783030260613

Category: Computers

Page: 580

View: 483

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This book constitutes the proceedings of the 21st International Conference on Speech and Computer, SPECOM 2019, held in Istanbul, Turkey, in August 2019. The 57 papers presented were carefully reviewed and selected from 86 submissions. The papers present current research in the area of computer speech processing including audio signal processing, automatic speech recognition, speaker recognition, computational paralinguistics, speech synthesis, sign language and multimodal processing, and speech and language resources.

Multimodal Behavior Analysis in the Wild

[69] D. Kounades-Bastian, L. Girin, X. Alameda-Pineda, S. Gannot, R. Horaud, Exploiting the intermittency of speech for joint separation and diarization, in: IEEE Workshop on Applications of Signal Processing to Audio and Acoustics ...

Author: Xavier Alameda-Pineda

Publisher: Academic Press

ISBN: 9780128146026

Category: Computers

Page: 498

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Multimodal Behavioral Analysis in the Wild: Advances and Challenges presents the state-of- the-art in behavioral signal processing using different data modalities, with a special focus on identifying the strengths and limitations of current technologies. The book focuses on audio and video modalities, while also emphasizing emerging modalities, such as accelerometer or proximity data. It covers tasks at different levels of complexity, from low level (speaker detection, sensorimotor links, source separation), through middle level (conversational group detection, addresser and addressee identification), and high level (personality and emotion recognition), providing insights on how to exploit inter-level and intra-level links. This is a valuable resource on the state-of-the- art and future research challenges of multi-modal behavioral analysis in the wild. It is suitable for researchers and graduate students in the fields of computer vision, audio processing, pattern recognition, machine learning and social signal processing. Gives a comprehensive collection of information on the state-of-the-art, limitations, and challenges associated with extracting behavioral cues from real-world scenarios Presents numerous applications on how different behavioral cues have been successfully extracted from different data sources Provides a wide variety of methodologies used to extract behavioral cues from multi-modal data

Latent Variable Analysis and Signal Separation

IEEE Transactions on Audio, Speech and Language Processing 14(4), 1218–1234 (2006) 5. Cohen, I.: Speech enhancement using a noncausal a priori SNR estimator. IEEE Signal Processing Letters 11(9) ...

Author: Vincent Vigneron

Publisher: Springer Science & Business Media

ISBN: 9783642159947

Category: Computers

Page: 655

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Thisvolumecollectsthepaperspresentedatthe9thInternationalConferenceon Latent Variable Analysis and Signal Separation,LVA/ICA 2010. The conference was organized by INRIA, the French National Institute for Computer Science and Control,and was held in Saint-Malo, France, September 27–30,2010,at the Palais du Grand Large. Tenyearsafterthe?rstworkshoponIndependent Component Analysis(ICA) in Aussois, France, the series of ICA conferences has shown the liveliness of the community of theoreticians and practitioners working in this ?eld. While ICA and blind signal separation have become mainstream topics, new approaches have emerged to solve problems involving signal mixtures or various other types of latent variables: semi-blind models, matrix factorization using sparse com- nent analysis, non-negative matrix factorization, probabilistic latent semantic indexing, tensor decompositions, independent vector analysis, independent s- space analysis, and so on. To re?ect this evolution towards more general latent variable analysis problems in signal processing, the ICA International Steering Committee decided to rename the 9th instance of the conference LVA/ICA. From more than a hundred submitted papers, 25 were accepted as oral p- sentationsand53 asposter presentations. Thecontent ofthis volumefollowsthe conference schedule, resulting in 14 chapters. The papers collected in this v- ume demonstrate that the research activity in the ?eld continues to range from abstract concepts to the most concrete and applicable questions and consid- ations. Speech and audio, as well as biomedical applications, continue to carry the mass of the applications considered.

Latent Variable Analysis and Signal Separation

Duong, H.T.T., Nguyen, Q.C., Nguyen, C.P., Tran, T.H., Duong, N.Q.K.: Speech enhancement based on nonnegative ... 276–280 (2015) Duong, N.Q.K., Vincent, E., Gribonval, R.: Under-determined reverberant audio source separation using a ...

Author: Yannick Deville

Publisher: Springer

ISBN: 9783319937649

Category: Computers

Page: 580

View: 989

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This book constitutes the proceedings of the 14th International Conference on Latent Variable Analysis and Signal Separation, LVA/ICA 2018, held in Guildford, UK, in July 2018.The 52 full papers were carefully reviewed and selected from 62 initial submissions. As research topics the papers encompass a wide range of general mixtures of latent variables models but also theories and tools drawn from a great variety of disciplines such as structured tensor decompositions and applications; matrix and tensor factorizations; ICA methods; nonlinear mixtures; audio data and methods; signal separation evaluation campaign; deep learning and data-driven methods; advances in phase retrieval and applications; sparsity-related methods; and biomedical data and methods.

Intelligent Audio Analysis

This book provides the reader with the knowledge necessary for comprehension of the field of Intelligent Audio Analysis.

Author: Björn W. Schuller

Publisher: Springer Science & Business Media

ISBN: 9783642368066

Category: Technology & Engineering

Page: 345

View: 492

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This book provides the reader with the knowledge necessary for comprehension of the field of Intelligent Audio Analysis. It firstly introduces standard methods and discusses the typical Intelligent Audio Analysis chain going from audio data to audio features to audio recognition. Further, an introduction to audio source separation, and enhancement and robustness are given. After the introductory parts, the book shows several applications for the three types of audio: speech, music, and general sound. Each task is shortly introduced, followed by a description of the specific data and methods applied, experiments and results, and a conclusion for this specific task. The books provides benchmark results and standardized test-beds for a broader range of audio analysis tasks. The main focus thereby lies on the parallel advancement of realism in audio analysis, as too often today’s results are overly optimistic owing to idealized testing conditions, and it serves to stimulate synergies arising from transfer of methods and leads to a holistic audio analysis.