2009 Ieee Workshop On Applications Of Signal Processing To Audio And Acoustics
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| Author | : Meinard Müller |
| Publisher | : Springer |
| Total Pages | : 509 |
| Release | : 2015-07-21 |
| Genre | : Computers |
| ISBN | : 3319219456 |
This textbook provides both profound technological knowledge and a comprehensive treatment of essential topics in music processing and music information retrieval. Including numerous examples, figures, and exercises, this book is suited for students, lecturers, and researchers working in audio engineering, computer science, multimedia, and musicology. The book consists of eight chapters. The first two cover foundations of music representations and the Fourier transform—concepts that are then used throughout the book. In the subsequent chapters, concrete music processing tasks serve as a starting point. Each of these chapters is organized in a similar fashion and starts with a general description of the music processing scenario at hand before integrating it into a wider context. It then discusses—in a mathematically rigorous way—important techniques and algorithms that are generally applicable to a wide range of analysis, classification, and retrieval problems. At the same time, the techniques are directly applied to a specific music processing task. By mixing theory and practice, the book’s goal is to offer detailed technological insights as well as a deep understanding of music processing applications. Each chapter ends with a section that includes links to the research literature, suggestions for further reading, a list of references, and exercises. The chapters are organized in a modular fashion, thus offering lecturers and readers many ways to choose, rearrange or supplement the material. Accordingly, selected chapters or individual sections can easily be integrated into courses on general multimedia, information science, signal processing, music informatics, or the digital humanities.
| Author | : Weinzierl, Stefan |
| Publisher | : Universitätsverlag der TU Berlin |
| Total Pages | : 200 |
| Release | : 2014 |
| Genre | : |
| ISBN | : 3798327041 |
In consideration of the remarkable intensity of research in the field of Virtual Acoustics, including different areas such as sound field analysis and synthesis, spatial audio technologies, and room acoustical modeling and auralization, it seemed about time to organize a second international symposium following the model of the first EAA Auralization Symposium initiated in 2009 by the acoustics group of the former Helsinki University of Technology (now Aalto University). Additionally, research communities which are focused on different approaches to sound field synthesis such as Ambisonics or Wave Field Synthesis have, in the meantime, moved closer together by using increasingly consistent theoretical frameworks. Finally, the quality of virtual acoustic environments is often considered as a result of all processing stages mentioned above, increasing the need for discussions on consistent strategies for evaluation. Thus, it seemed appropriate to integrate two of the most relevant communities, i.e. to combine the 2nd International Auralization Symposium with the 5th International Symposium on Ambisonics and Spherical Acoustics. The Symposia on Ambisonics, initiated in 2009 by the Institute of Electronic Music and Acoustics of the University of Music and Performing Arts in Graz, were traditionally dedicated to problems of spherical sound field analysis and re-synthesis, strategies for the exchange of ambisonics-encoded audio material, and – more than other conferences in this area – the artistic application of spatial audio systems. This publication contains the official conference proceedings. It includes 29 manuscripts which have passed a 3-stage peer-review with a board of about 70 international reviewers involved in the process. Each contribution has already been published individually with a unique DOI on the DepositOnce digital repository of TU Berlin. Some conference contributions have been recommended for resubmission to Acta Acustica united with Acustica, to possibly appear in a Special Issue on Virtual Acoustics in late 2014. These are not published in this collection.
| Author | : Emmanuel Vincent |
| Publisher | : John Wiley & Sons |
| Total Pages | : 517 |
| Release | : 2018-10-22 |
| Genre | : Technology & Engineering |
| ISBN | : 1119279895 |
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.
| Author | : Wang, Wenwu |
| Publisher | : IGI Global |
| Total Pages | : 554 |
| Release | : 2010-07-31 |
| Genre | : Computers |
| ISBN | : 1615209204 |
Machine audition is the study of algorithms and systems for the automatic analysis and understanding of sound by machine. It has recently attracted increasing interest within several research communities, such as signal processing, machine learning, auditory modeling, perception and cognition, psychology, pattern recognition, and artificial intelligence. However, the developments made so far are fragmented within these disciplines, lacking connections and incurring potentially overlapping research activities in this subject area. Machine Audition: Principles, Algorithms and Systems contains advances in algorithmic developments, theoretical frameworks, and experimental research findings. This book is useful for professionals who want an improved understanding about how to design algorithms for performing automatic analysis of audio signals, construct a computing system for understanding sound, and learn how to build advanced human-computer interactive systems.
| Author | : Ville Pulkki |
| Publisher | : John Wiley & Sons |
| Total Pages | : 498 |
| Release | : 2017-10-11 |
| Genre | : Technology & Engineering |
| ISBN | : 111925261X |
A comprehensive guide that addresses the theory and practice of spatial audio This book provides readers with the principles and best practices in spatial audio signal processing. It describes how sound fields and their perceptual attributes are captured and analyzed within the time-frequency domain, how essential representation parameters are coded, and how such signals are efficiently reproduced for practical applications. The book is split into four parts starting with an overview of the fundamentals. It then goes on to explain the reproduction of spatial sound before offering an examination of signal-dependent spatial filtering. The book finishes with coverage of both current and future applications and the direction that spatial audio research is heading in. Parametric Time-frequency Domain Spatial Audio focuses on applications in entertainment audio, including music, home cinema, and gaming—covering the capturing and reproduction of spatial sound as well as its generation, transduction, representation, transmission, and perception. This book will teach readers the tools needed for such processing, and provides an overview to existing research. It also shows recent up-to-date projects and commercial applications built on top of the systems. Provides an in-depth presentation of the principles, past developments, state-of-the-art methods, and future research directions of spatial audio technologies Includes contributions from leading researchers in the field Offers MATLAB codes with selected chapters An advanced book aimed at readers who are capable of digesting mathematical expressions about digital signal processing and sound field analysis, Parametric Time-frequency Domain Spatial Audio is best suited for researchers in academia and in the audio industry.
| Author | : Solvi Ystad |
| Publisher | : Springer Science & Business Media |
| Total Pages | : 370 |
| Release | : 2011-09-15 |
| Genre | : Computers |
| ISBN | : 364223125X |
This book constitutes the thoroughly refereed post-proceedings of the 7th International Symposium on Computer Music Modeling and Retrieval, CMMR 2010, held in Málaga, Spain, in June 2010. The 22 revised full papers presented were specially reviewed and revised for inclusion in this proceedings volume. The book is divided in five main chapters which reflect the present challenges within the field of computer music modeling and retrieval. The chapters range from music interaction, composition tools and sound source separation to data mining and music libraries. One chapter is also dedicated to perceptual and cognitive aspects that are currently subject to increased interest in the MIR community.
| Author | : Ganesh R. Naik |
| Publisher | : BoD – Books on Demand |
| Total Pages | : 360 |
| Release | : 2012-10-10 |
| Genre | : Medical |
| ISBN | : 9535107828 |
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.
| Author | : Xavier Alameda-Pineda |
| Publisher | : Academic Press |
| Total Pages | : 500 |
| Release | : 2018-11-13 |
| Genre | : Technology & Engineering |
| ISBN | : 0128146028 |
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
| Author | : Siddhartha Bhattacharyya |
| Publisher | : Walter de Gruyter GmbH & Co KG |
| Total Pages | : 170 |
| Release | : 2020-06-22 |
| Genre | : Computers |
| ISBN | : 3110670909 |
This book focuses on the fundamentals of deep learning along with reporting on the current state-of-art research on deep learning. In addition, it provides an insight of deep neural networks in action with illustrative coding examples. Deep learning is a new area of machine learning research which has been introduced with the objective of moving ML closer to one of its original goals, i.e. artificial intelligence. Deep learning was developed as an ML approach to deal with complex input-output mappings. While traditional methods successfully solve problems where final value is a simple function of input data, deep learning techniques are able to capture composite relations between non-immediately related fields, for example between air pressure recordings and English words, millions of pixels and textual description, brand-related news and future stock prices and almost all real world problems. Deep learning is a class of nature inspired machine learning algorithms that uses a cascade of multiple layers of nonlinear processing units for feature extraction and transformation. Each successive layer uses the output from the previous layer as input. The learning may be supervised (e.g. classification) and/or unsupervised (e.g. pattern analysis) manners. These algorithms learn multiple levels of representations that correspond to different levels of abstraction by resorting to some form of gradient descent for training via backpropagation. Layers that have been used in deep learning include hidden layers of an artificial neural network and sets of propositional formulas. They may also include latent variables organized layer-wise in deep generative models such as the nodes in deep belief networks and deep boltzmann machines. Deep learning is part of state-of-the-art systems in various disciplines, particularly computer vision, automatic speech recognition (ASR) and human action recognition.
| Author | : Vladimir Britanak |
| Publisher | : Springer |
| Total Pages | : 664 |
| Release | : 2017-08-02 |
| Genre | : Technology & Engineering |
| ISBN | : 3319610805 |
This book covers various algorithmic developments in the perfect reconstruction cosine/sine-modulated filter banks (TDAC-MDCT/MDST or MLT, MCLT, low delay MDCT, complex exponential/cosine/sine-modulated QMF filter banks), and near-perfect reconstruction QMF banks (pseudo-QMF banks) in detail, including their general mathematical properties, matrix representations, fast algorithms and various methods to integer approximations being recently a new transform technology for lossless audio coding. Each chapter will contain a number of examples and will conclude with problems and exercises. The book reflects the research efforts/activities and achieved results of the authors in the time period over the last 20 years.
