Blind Speech Separation
DOWNLOAD
Download Blind Speech Separation PDF/ePub or read online books in Mobi eBooks. Click Download or Read Online button to get Blind Speech Separation book now. This website allows unlimited access to, at the time of writing, more than 1.5 million titles, including hundreds of thousands of titles in various foreign languages. If the content not found or just blank you must refresh this page
Blind Speech Separation
DOWNLOAD
Author : Shoji Makino
language : en
Publisher: Springer Science & Business Media
Release Date : 2007-09-07
Blind Speech Separation written by Shoji Makino and has been published by Springer Science & Business Media this book supported file pdf, txt, epub, kindle and other format this book has been release on 2007-09-07 with Technology & Engineering categories.
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.
Audio Source Separation
DOWNLOAD
Author : Shoji Makino
language : en
Publisher: Springer
Release Date : 2018-03-01
Audio Source Separation written by Shoji Makino and has been published by Springer this book supported file pdf, txt, epub, kindle and other format this book has been release on 2018-03-01 with Technology & Engineering categories.
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.
Speech Separation By Humans And Machines
DOWNLOAD
Author : Pierre Divenyi
language : en
Publisher: Springer Science & Business Media
Release Date : 2006-01-16
Speech Separation By Humans And Machines written by Pierre Divenyi and has been published by Springer Science & Business Media this book supported file pdf, txt, epub, kindle and other format this book has been release on 2006-01-16 with Technology & Engineering categories.
There is a serious problem in the recognition of sounds. It derives from the fact that they do not usually occur in isolation but in an environment in which a number of sound sources (voices, traffic, footsteps, music on the radio, and so on) are active at the same time. When these sounds arrive at the ear of the listener, the complex pressure waves coming from the separate sources add together to produce a single, more complex pressure wave that is the sum of the individual waves. The problem is how to form separate mental descriptions of the component sounds, despite the fact that the “mixture wave” does not directly reveal the waves that have been summed to form it. The name auditory scene analysis (ASA) refers to the process whereby the auditory systems of humans and other animals are able to solve this mixture problem. The process is believed to be quite general, not specific to speech sounds or any other type of sounds, and to exist in many species other than humans. It seems to involve assigning spectral energy to distinct “auditory objects” and “streams” that serve as the mental representations of distinct sound sources in the environment and the patterns that they make as they change over time. How this energy is assigned will affect the perceived n- ber of auditory sources, their perceived timbres, loudnesses, positions in space, and pitches.
Blind Source Separation
DOWNLOAD
Author : Xianchuan Yu
language : en
Publisher: John Wiley & Sons
Release Date : 2014-01-28
Blind Source Separation written by Xianchuan Yu and has been published by John Wiley & Sons this book supported file pdf, txt, epub, kindle and other format this book has been release on 2014-01-28 with Technology & Engineering categories.
A systematic exploration of both classic and contemporary algorithms in blind source separation with practical case studies The book presents an overview of Blind Source Separation, a relatively new signal processing method. Due to the multidisciplinary nature of the subject, the book has been written so as to appeal to an audience from very different backgrounds. Basic mathematical skills (e.g. on matrix algebra and foundations of probability theory) are essential in order to understand the algorithms, although the book is written in an introductory, accessible style. This book offers a general overview of the basics of Blind Source Separation, important solutions and algorithms, and in-depth coverage of applications in image feature extraction, remote sensing image fusion, mixed-pixel decomposition of SAR images, image object recognition fMRI medical image processing, geochemical and geophysical data mining, mineral resources prediction and geoanomalies information recognition. Firstly, the background and theory basics of blind source separation are introduced, which provides the foundation for the following work. Matrix operation, foundations of probability theory and information theory basics are included here. There follows the fundamental mathematical model and fairly new but relatively established blind source separation algorithms, such as Independent Component Analysis (ICA) and its improved algorithms (Fast ICA, Maximum Likelihood ICA, Overcomplete ICA, Kernel ICA, Flexible ICA, Non-negative ICA, Constrained ICA, Optimised ICA). The last part of the book considers the very recent algorithms in BSS e.g. Sparse Component Analysis (SCA) and Non-negative Matrix Factorization (NMF). Meanwhile, in-depth cases are presented for each algorithm in order to help the reader understand the algorithm and its application field. A systematic exploration of both classic and contemporary algorithms in blind source separation with practical case studies Presents new improved algorithms aimed at different applications, such as image feature extraction, remote sensing image fusion, mixed-pixel decomposition of SAR images, image object recognition, and MRI medical image processing With applications in geochemical and geophysical data mining, mineral resources prediction and geoanomalies information recognition Written by an expert team with accredited innovations in blind source separation and its applications in natural science Accompanying website includes a software system providing codes for most of the algorithms mentioned in the book, enhancing the learning experience Essential reading for postgraduate students and researchers engaged in the area of signal processing, data mining, image processing and recognition, information, geosciences, life sciences.
Nonlinear Blind Source Separation And Blind Mixture Identification
DOWNLOAD
Author : Yannick Deville
language : en
Publisher: Springer Nature
Release Date : 2021-02-02
Nonlinear Blind Source Separation And Blind Mixture Identification written by Yannick Deville and has been published by Springer Nature this book supported file pdf, txt, epub, kindle and other format this book has been release on 2021-02-02 with Technology & Engineering categories.
This book provides a detailed survey of the methods that were recently developed to handle advanced versions of the blind source separation problem, which involve several types of nonlinear mixtures. Another attractive feature of the book is that it is based on a coherent framework. More precisely, the authors first present a general procedure for developing blind source separation methods. Then, all reported methods are defined with respect to this procedure. This allows the reader not only to more easily follow the description of each method but also to see how these methods relate to one another. The coherence of this book also results from the fact that the same notations are used throughout the chapters for the quantities (source signals and so on) that are used in various methods. Finally, among the quite varied types of processing methods that are presented in this book, a significant part of this description is dedicated to methods based on artificial neural networks, especially recurrent ones, which are currently of high interest to the data analysis and machine learning community in general, beyond the more specific signal processing and blind source separation communities.
Blind Speech Separation In Distant Speech Recognition Front End Processing
DOWNLOAD
Author : Rahil Mahdian Toroghi
language : en
Publisher:
Release Date : 2016
Blind Speech Separation In Distant Speech Recognition Front End Processing written by Rahil Mahdian Toroghi and has been published by this book supported file pdf, txt, epub, kindle and other format this book has been release on 2016 with categories.
Audio Source Separation And Speech Enhancement
DOWNLOAD
Author : Emmanuel Vincent
language : en
Publisher: John Wiley & Sons
Release Date : 2018-10-22
Audio Source Separation And Speech Enhancement written by Emmanuel Vincent and has been published by John Wiley & Sons this book supported file pdf, txt, epub, kindle and other format this book has been release on 2018-10-22 with Technology & Engineering categories.
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.
Techniques For Noise Robustness In Automatic Speech Recognition
DOWNLOAD
Author : Tuomas Virtanen
language : en
Publisher: John Wiley & Sons
Release Date : 2012-11-28
Techniques For Noise Robustness In Automatic Speech Recognition written by Tuomas Virtanen and has been published by John Wiley & Sons this book supported file pdf, txt, epub, kindle and other format this book has been release on 2012-11-28 with Technology & Engineering categories.
Automatic speech recognition (ASR) systems are finding increasing use in everyday life. Many of the commonplace environments where the systems are used are noisy, for example users calling up a voice search system from a busy cafeteria or a street. This can result in degraded speech recordings and adversely affect the performance of speech recognition systems. As the use of ASR systems increases, knowledge of the state-of-the-art in techniques to deal with such problems becomes critical to system and application engineers and researchers who work with or on ASR technologies. This book presents a comprehensive survey of the state-of-the-art in techniques used to improve the robustness of speech recognition systems to these degrading external influences. Key features: Reviews all the main noise robust ASR approaches, including signal separation, voice activity detection, robust feature extraction, model compensation and adaptation, missing data techniques and recognition of reverberant speech. Acts as a timely exposition of the topic in light of more widespread use in the future of ASR technology in challenging environments. Addresses robustness issues and signal degradation which are both key requirements for practitioners of ASR. Includes contributions from top ASR researchers from leading research units in the field
Springer Handbook Of Speech Processing
DOWNLOAD
Author : Jacob Benesty
language : en
Publisher: Springer Science & Business Media
Release Date : 2007-11-28
Springer Handbook Of Speech Processing written by Jacob Benesty and has been published by Springer Science & Business Media this book supported file pdf, txt, epub, kindle and other format this book has been release on 2007-11-28 with Technology & Engineering categories.
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.
Source Separation And Machine Learning
DOWNLOAD
Author : Jen-Tzung Chien
language : en
Publisher: Academic Press
Release Date : 2018-10-16
Source Separation And Machine Learning written by Jen-Tzung Chien and has been published by Academic Press this book supported file pdf, txt, epub, kindle and other format this book has been release on 2018-10-16 with Technology & Engineering categories.
Source Separation and Machine Learning presents the fundamentals in adaptive learning algorithms for Blind Source Separation (BSS) and emphasizes the importance of machine learning perspectives. It illustrates how BSS problems are tackled through adaptive learning algorithms and model-based approaches using the latest information on mixture signals to build a BSS model that is seen as a statistical model for a whole system. Looking at different models, including independent component analysis (ICA), nonnegative matrix factorization (NMF), nonnegative tensor factorization (NTF), and deep neural network (DNN), the book addresses how they have evolved to deal with multichannel and single-channel source separation. - Emphasizes the modern model-based Blind Source Separation (BSS) which closely connects the latest research topics of BSS and Machine Learning - Includes coverage of Bayesian learning, sparse learning, online learning, discriminative learning and deep learning - Presents a number of case studies of model-based BSS (categorizing them into four modern models - ICA, NMF, NTF and DNN), using a variety of learning algorithms that provide solutions for the construction of BSS systems