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EBookClubs

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Book Model based Speech Enhancement Exploiting Temporal and Spectral Dependencies

Download or read book Model based Speech Enhancement Exploiting Temporal and Spectral Dependencies written by Thomas Esch and published by . This book was released on 2012 with total page 162 pages. Available in PDF, EPUB and Kindle. Book excerpt:

Book Speech Enhancement

Download or read book Speech Enhancement written by Jacob Benesty and published by Elsevier. This book was released on 2014-01-04 with total page 143 pages. Available in PDF, EPUB and Kindle. Book excerpt: Speech enhancement is a classical problem in signal processing, yet still largely unsolved. Two of the conventional approaches for solving this problem are linear filtering, like the classical Wiener filter, and subspace methods. These approaches have traditionally been treated as different classes of methods and have been introduced in somewhat different contexts. Linear filtering methods originate in stochastic processes, while subspace methods have largely been based on developments in numerical linear algebra and matrix approximation theory. This book bridges the gap between these two classes of methods by showing how the ideas behind subspace methods can be incorporated into traditional linear filtering. In the context of subspace methods, the enhancement problem can then be seen as a classical linear filter design problem. This means that various solutions can more easily be compared and their performance bounded and assessed in terms of noise reduction and speech distortion. The book shows how various filter designs can be obtained in this framework, including the maximum SNR, Wiener, LCMV, and MVDR filters, and how these can be applied in various contexts, like in single-channel and multichannel speech enhancement, and in both the time and frequency domains. - First short book treating subspace approaches in a unified way for time and frequency domains, single-channel, multichannel, as well as binaural, speech enhancement - Bridges the gap between optimal filtering methods and subspace approaches - Includes original presentation of subspace methods from different perspectives

Book Perceptual and Multi microphone Signal Subspace Techniques for Speech Enhancement

Download or read book Perceptual and Multi microphone Signal Subspace Techniques for Speech Enhancement written by Firas Jabloun and published by . This book was released on 2004 with total page pages. Available in PDF, EPUB and Kindle. Book excerpt:

Book Speech Enhancement

Download or read book Speech Enhancement written by Philipos C. Loizou and published by CRC Press. This book was released on 2007-06-07 with total page 640 pages. Available in PDF, EPUB and Kindle. Book excerpt: This book covers traditional speech enhancement algorithms, such as spectral subtraction and Wiener filtering algorithms as well as state-of-the-art algorithms including minimum mean-squared error algorithms that incorporate signal-presence uncertainty and subspace algorithms that incorporate psychoacoustic models. The coverage includes objective and subjective measures used to evaluate speech quality and intelligibility. Divided into three parts, the book presents the digital-signal processing and speech signal fundamentals needed to understand speech enhancement algorithms, the various classes of speech enhancement algorithms proposed over the last two decades, and the methods and measures used to evaluate the performance of speech enhancement algorithms.

Book Speech Enhancement

Download or read book Speech Enhancement written by Philipos C. Loizou and published by CRC Press. This book was released on 2013-02-25 with total page 715 pages. Available in PDF, EPUB and Kindle. Book excerpt: With the proliferation of mobile devices and hearing devices, including hearing aids and cochlear implants, there is a growing and pressing need to design algorithms that can improve speech intelligibility without sacrificing quality. Responding to this need, Speech Enhancement: Theory and Practice, Second Edition introduces readers to the basic problems of speech enhancement and the various algorithms proposed to solve these problems. Updated and expanded, this second edition of the bestselling textbook broadens its scope to include evaluation measures and enhancement algorithms aimed at improving speech intelligibility. Fundamentals, Algorithms, Evaluation, and Future Steps Organized into four parts, the book begins with a review of the fundamentals needed to understand and design better speech enhancement algorithms. The second part describes all the major enhancement algorithms and, because these require an estimate of the noise spectrum, also covers noise estimation algorithms. The third part of the book looks at the measures used to assess the performance, in terms of speech quality and intelligibility, of speech enhancement methods. It also evaluates and compares several of the algorithms. The fourth part presents binary mask algorithms for improving speech intelligibility under ideal conditions. In addition, it suggests steps that can be taken to realize the full potential of these algorithms under realistic conditions. What’s New in This Edition Updates in every chapter A new chapter on objective speech intelligibility measures A new chapter on algorithms for improving speech intelligibility Real-world noise recordings (on accompanying CD) MATLAB® code for the implementation of intelligibility measures (on accompanying CD) MATLAB and C/C++ code for the implementation of algorithms to improve speech intelligibility (on accompanying CD) Valuable Insights from a Pioneer in Speech Enhancement Clear and concise, this book explores how human listeners compensate for acoustic noise in noisy environments. Written by a pioneer in speech enhancement and noise reduction in cochlear implants, it is an essential resource for anyone who wants to implement or incorporate the latest speech enhancement algorithms to improve the quality and intelligibility of speech degraded by noise. Includes a CD with Code and Recordings The accompanying CD provides MATLAB implementations of representative speech enhancement algorithms as well as speech and noise databases for the evaluation of enhancement algorithms.

Book Speech Enhancement Methods Based on CASA Incorporating Spectral Correlation

Download or read book Speech Enhancement Methods Based on CASA Incorporating Spectral Correlation written by Feng Bao and published by . This book was released on 2018 with total page 141 pages. Available in PDF, EPUB and Kindle. Book excerpt: Computational auditory scene analysis (CASA) has shown a great potential for speech enhancement compared to some statistical model-based methods. A challenge for CASA is how to estimate binary mask or ratio mask effectively in each time-frequency (T-F) unit. In this thesis, four speech enhancement methods with binary mask or ratio mask estimation are proposed based on the spectral relationship among noisy speech, pure noise and clean speech. The common use of fixed thresholds in the conventional CASA method constrains segregation and T-F unit labeling, affecting the performance of de-noising. Thus, an adaptive factor is first derived from the power spectra of noisy speech and estimated noise to replace those fixed thresholds. As a result, noise reduction is achieved with improved pitch contour and T-F unit labeling. A new binary mask estimation method is proposed based on convex optimization to reduce artifacts and temporal discontinuity caused by the inaccuracy of binary mask estimation. Signal segregation and pitch estimation are not needed in this method; only speech power is considered as a key cue for labeling the binary mask. The cross-correlation between the noisy speech and estimated noise power spectra in each channel is employed to build the objective function. The T-F units of speech and noise are labeled with a decision factor derived from the powers of noisy speech, estimated speech, and pre-estimated noise respectively. Erroneous local masks are refined by time-frequency unit smoothing. As a consequence, noise is effectively reduced and the perceptual quality of the enhanced speech is improved. A new estimation method of ratio mask in terms of Wiener filtering is proposed in order to further increase the temporal continuity of reconstructed speech. In this method, the speech power of each T-F unit is obtained by a convex optimization method. The objective function depends also on the cross-correlation between the noisy speech and estimated noise power spectra. To improve the accuracy of estimation, the estimated ratio mask is further modified based on its adjacent time-frequency units and then smoothed by interpolating with the estimated binary masks. The results confirmed that the performances related to noise reduction, speech quality, and speech intelligibility are all improved. A novel ratio mask representation by exploiting the inter-channel correlation (ICC) among the noisy speech, pure noise and clean speech spectra is proposed to further improve enhancement performance. In this way, the power ratio of speech and noise is reallocated adaptively during the construction of ratio mask, so that more speech components are retained and more noise components are masked. In this method, the channel-weight contour based on the equal loudness hearing attribute is adopted to revise the ratio mask in each T-F unit. The developed ratio mask is utilized to train a five-layer Deep Neural Network (DNN) with other features. Experiments show significant improvements in speech quality and intelligibility compared to DNN-based methods without ICC.

Book Signal Subspace based Speech Enhancement

Download or read book Signal Subspace based Speech Enhancement written by Chung-Jen Kuo and published by . This book was released on 2001 with total page 258 pages. Available in PDF, EPUB and Kindle. Book excerpt:

Book ICT with Intelligent Applications

Download or read book ICT with Intelligent Applications written by Tomonobu Senjyu and published by Springer Nature. This book was released on 2021-12-05 with total page 802 pages. Available in PDF, EPUB and Kindle. Book excerpt: This book gathers papers addressing state-of-the-art research in all areas of information and communication technologies and their applications in intelligent computing, cloud storage, data mining and software analysis. It presents the outcomes of the Fifth International Conference on Information and Communication Technology for Intelligent Systems (ICTIS 2021), held in Ahmedabad, India. The book is divided into two volumes. It discusses the fundamentals of various data analysis techniques and algorithms, making it a valuable resource for researchers and practitioners alike.

Book Speech Dereverberation

Download or read book Speech Dereverberation written by Patrick A. Naylor and published by Springer Science & Business Media. This book was released on 2010-07-27 with total page 388 pages. Available in PDF, EPUB and Kindle. Book excerpt: 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.

Book Springer Handbook of Speech Processing

Download or read book Springer Handbook of Speech Processing written by Jacob Benesty and published by Springer Science & Business Media. This book was released on 2007-11-28 with total page 1170 pages. Available in PDF, EPUB and Kindle. Book excerpt: 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.

Book Subspace Identification for Linear Systems

Download or read book Subspace Identification for Linear Systems written by Peter van Overschee and published by Springer Science & Business Media. This book was released on 2012-12-06 with total page 263 pages. Available in PDF, EPUB and Kindle. Book excerpt: Subspace Identification for Linear Systems focuses on the theory, implementation and applications of subspace identification algorithms for linear time-invariant finite- dimensional dynamical systems. These algorithms allow for a fast, straightforward and accurate determination of linear multivariable models from measured input-output data. The theory of subspace identification algorithms is presented in detail. Several chapters are devoted to deterministic, stochastic and combined deterministic-stochastic subspace identification algorithms. For each case, the geometric properties are stated in a main 'subspace' Theorem. Relations to existing algorithms and literature are explored, as are the interconnections between different subspace algorithms. The subspace identification theory is linked to the theory of frequency weighted model reduction, which leads to new interpretations and insights. The implementation of subspace identification algorithms is discussed in terms of the robust and computationally efficient RQ and singular value decompositions, which are well-established algorithms from numerical linear algebra. The algorithms are implemented in combination with a whole set of classical identification algorithms, processing and validation tools in Xmath's ISID, a commercially available graphical user interface toolbox. The basic subspace algorithms in the book are also implemented in a set of Matlab files accompanying the book. An application of ISID to an industrial glass tube manufacturing process is presented in detail, illustrating the power and user-friendliness of the subspace identification algorithms and of their implementation in ISID. The identified model allows for an optimal control of the process, leading to a significant enhancement of the production quality. The applicability of subspace identification algorithms in industry is further illustrated with the application of the Matlab files to ten practical problems. Since all necessary data and Matlab files are included, the reader can easily step through these applications, and thus get more insight in the algorithms. Subspace Identification for Linear Systems is an important reference for all researchers in system theory, control theory, signal processing, automization, mechatronics, chemical, electrical, mechanical and aeronautical engineering.

Book Speech Enhancement in the STFT Domain

Download or read book Speech Enhancement in the STFT Domain written by Jacob Benesty and published by Springer Science & Business Media. This book was released on 2011-09-18 with total page 112 pages. Available in PDF, EPUB and Kindle. Book excerpt: This work addresses this problem in the short-time Fourier transform (STFT) domain. We divide the general problem into five basic categories depending on the number of microphones being used and whether the interframe or interband correlation is considered. The first category deals with the single-channel problem where STFT coefficients at different frames and frequency bands are assumed to be independent. In this case, the noise reduction filter in each frequency band is basically a real gain. Since a gain does not improve the signal-to-noise ratio (SNR) for any given subband and frame, the noise reduction is basically achieved by liftering the subbands and frames that are less noisy while weighing down on those that are more noisy. The second category also concerns the single-channel problem. The difference is that now the interframe correlation is taken into account and a filter is applied in each subband instead of just a gain. The advantage of using the interframe correlation is that we can improve not only the long-time fullband SNR, but the frame-wise subband SNR as well. The third and fourth classes discuss the problem of multichannel noise reduction in the STFT domain with and without interframe correlation, respectively. In the last category, we consider the interband correlation in the design of the noise reduction filters. We illustrate the basic principle for the single-channel case as an example, while this concept can be generalized to other scenarios. In all categories, we propose different optimization cost functions from which we derive the optimal filters and we also define the performance measures that help analyzing them.

Book Multidimensional Systems  Signal Processing and Modeling Techniques

Download or read book Multidimensional Systems Signal Processing and Modeling Techniques written by and published by Elsevier. This book was released on 1995-07-13 with total page 455 pages. Available in PDF, EPUB and Kindle. Book excerpt: Praise for Previous Volumes"This book will be a useful reference to control engineers and researchers. The papers contained cover well the recent advances in the field of modern control theory."-IEEE CONTROL CORRESPONDANCE" This book will help all those researchers wjo valiantly try to keep abreast of what is new in the theory and practice of optimal control."-CONTROL

Book The Application of Hidden Markov Models in Speech Recognition

Download or read book The Application of Hidden Markov Models in Speech Recognition written by Mark Gales and published by Now Publishers Inc. This book was released on 2008 with total page 125 pages. Available in PDF, EPUB and Kindle. Book excerpt: The Application of Hidden Markov Models in Speech Recognition presents the core architecture of a HMM-based LVCSR system and proceeds to describe the various refinements which are needed to achieve state-of-the-art performance.

Book Index to IEEE Publications

Download or read book Index to IEEE Publications written by Institute of Electrical and Electronics Engineers and published by . This book was released on 1998 with total page 1234 pages. Available in PDF, EPUB and Kindle. Book excerpt: Issues for 1973- cover the entire IEEE technical literature.

Book Audio Source Separation and Speech Enhancement

Download or read book Audio Source Separation and Speech Enhancement written by Emmanuel Vincent and published by John Wiley & Sons. This book was released on 2018-10-22 with total page 517 pages. Available in PDF, EPUB and Kindle. Book excerpt: 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.