Speech Enhancement

Speech Enhancement
Author: Philipos C. Loizou
Publsiher: CRC Press
Total Pages: 711
Release: 2013-02-25
ISBN 10: 1466599227
ISBN 13: 9781466599222
Language: EN, FR, DE, ES & NL

Speech Enhancement Book Review:

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 pr

Speech Enhancement

Speech Enhancement
Author: Jacob Benesty,Shoji Makino,Jingdong Chen
Publsiher: Springer Science & Business Media
Total Pages: 406
Release: 2006-03-30
ISBN 10: 3540274898
ISBN 13: 9783540274896
Language: EN, FR, DE, ES & NL

Speech Enhancement Book Review:

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.

DFT Domain Based Single Microphone Noise Reduction for Speech Enhancement

DFT Domain Based Single Microphone Noise Reduction for Speech Enhancement
Author: Richard C. Hendriks,Timo Gerkmann,Jesper Jensen
Publsiher: Morgan & Claypool Publishers
Total Pages: 80
Release: 2013-01-01
ISBN 10: 1627051449
ISBN 13: 9781627051446
Language: EN, FR, DE, ES & NL

DFT Domain Based Single Microphone Noise Reduction for Speech Enhancement Book Review:

As speech processing devices like mobile phones, voice controlled devices, and hearing aids have increased in popularity, people expect them to work anywhere and at any time without user intervention. However, the presence of acoustical disturbances limits the use of these applications, degrades their performance, or causes the user difficulties in understanding the conversation or appreciating the device. A common way to reduce the effects of such disturbances is through the use of single-microphone noise reduction algorithms for speech enhancement. The field of single-microphone noise reduction for speech enhancement comprises a history of more than 30 years of research. In this survey, we wish to demonstrate the significant advances that have been made during the last decade in the field of discrete Fourier transform domain-based single-channel noise reduction for speech enhancement.Furthermore, our goal is to provide a concise description of a state-of-the-art speech enhancement system, and demonstrate the relative importance of the various building blocks of such a system. This allows the non-expert DSP practitioner to judge the relevance of each building block and to implement a close-to-optimal enhancement system for the particular application at hand. Table of Contents: Introduction / Single Channel Speech Enhancement: General Principles / DFT-Based Speech Enhancement Methods: Signal Model and Notation / Speech DFT Estimators / Speech Presence Probability Estimation / Noise PSD Estimation / Speech PSD Estimation / Performance Evaluation Methods / Simulation Experiments with Single-Channel Enhancement Systems / Future Directions

Speech Enhancement with Adaptive Thresholding and Kalman Filtering

Speech Enhancement with Adaptive Thresholding and Kalman Filtering
Author: Mengjiao Zhao
Publsiher: Unknown
Total Pages: 85
Release: 2018
ISBN 10:
ISBN 13: OCLC:1135024008
Language: EN, FR, DE, ES & NL

Speech Enhancement with Adaptive Thresholding and Kalman Filtering Book Review:

Speech enhancement has been extensively studied for many years and various speech enhancement methods have been developed during the past decades. One of the objectives of speech enhancement is to provide high-quality speech communication in the presence of background noise and concurrent interference signals. In the process of speech communication, the clean speech sig- nal is inevitably corrupted by acoustic noise from the surrounding environment, transmission media, communication equipment, electrical noise, other speakers, and other sources of interference. These disturbances can significantly degrade the quality and intelligibility of the received speech signal. Therefore, it is of great interest to develop efficient speech enhancement techniques to recover the original speech from the noisy observation. In recent years, various techniques have been developed to tackle this problem, which can be classified into single channel and multi-channel enhancement approaches. Since single channel enhancement is easy to implement, it has been a significant field of research and various approaches have been developed. For example, spectral subtraction and Wiener filtering, are among the earliest single channel methods, which are based on estimation of the power spectrum of stationary noise. However, when the noise is non-stationary, or there exists music noise and ambient speech noise, the enhancement performance would degrade considerably. To overcome this disadvantage, this thesis focuses on single channel speech enhancement under adverse noise environment, especially the non-stationary noise environment. Recently, wavelet transform based methods have been widely used to reduce the undesired background noise. On the other hand, the Kalman filter (KF) methods offer competitive denoising results, especially in non-stationary environment. It has been used as a popular and powerful tool for speech enhancement during the past decades. In this regard, a single channel wavelet thresholding based Kalman filter (KF) algorithm is proposed for speech enhancement in this thesis. The wavelet packet (WP) transform is first applied to the noise corrupted speech on a frame-by-frame basis, which decomposes each frame into a number of subbands. A voice activity detector (VAD) is then designed to detect the voiced/unvoiced frames of the subband speech. Based on the VAD result, an adaptive thresholding scheme is applied to each subband speech followed by the WP based reconstruction to obtain the pre-enhanced speech. To achieve a further level of enhancement, an iterative Kalman filter (IKF) is used to process the pre-enhanced speech. The proposed adaptive thresholding iterative Kalman filtering (AT-IKF) method is evaluated and compared with some existing methods under various noise conditions in terms of segmental SNR and perceptual evaluation of speech quality (PESQ) as two well-known performance indexes. Firstly, we compare the proposed adaptive thresholding (AT) scheme with three other threshold- ing schemes: the non-linear universal thresholding (U-T), the non-linear wavelet packet transform thresholding (WPT-T) and the non-linear SURE thresholding (SURE-T). The experimental results show that the proposed AT scheme can significantly improve the segmental SNR and PESQ for all input SNRs compared with the other existing thresholding schemes. Secondly, extensive computer simulations are conducted to evaluate the proposed AT-IKF as opposed to the AT and the IKF as standalone speech enhancement methods. It is shown that the AT-IKF method still performs the best. Lastly, the proposed ATIKF method is compared with three representative and popular meth- ods: the improved spectral subtraction based speech enhancement algorithm (ISS), the improved Wiener filter based method (IWF) and the representative subband Kalman filter based algorithm (SIKF). Experimental results demonstrate the effectiveness of the proposed method as compared to some previous works both in terms of segmental SNR and PESQ.

Speech Enhancement

Speech Enhancement
Author: Jacob Benesty,Jesper Rindom Jensen,Mads Graesboll Christensen,Jingdong Chen
Publsiher: Elsevier
Total Pages: 138
Release: 2014-01-04
ISBN 10: 0128002530
ISBN 13: 9780128002537
Language: EN, FR, DE, ES & NL

Speech Enhancement Book Review:

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

Audio Source Separation and Speech Enhancement

Audio Source Separation and Speech Enhancement
Author: Emmanuel Vincent,Tuomas Virtanen,Sharon Gannot
Publsiher: John Wiley & Sons
Total Pages: 504
Release: 2018-07-24
ISBN 10: 1119279917
ISBN 13: 9781119279914
Language: EN, FR, DE, ES & NL

Audio Source Separation and Speech Enhancement Book Review:

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.

Fractional Fourier Transform Techniques for Speech Enhancement

Fractional Fourier Transform Techniques for Speech Enhancement
Author: Prajna Kunche
Publsiher: Springer Nature
Total Pages: 329
Release: 2021
ISBN 10: 3030427463
ISBN 13: 9783030427467
Language: EN, FR, DE, ES & NL

Fractional Fourier Transform Techniques for Speech Enhancement Book Review:

Speech Enhancement

Speech Enhancement
Author: Jae S. Lim
Publsiher: Prentice Hall
Total Pages: 363
Release: 1983
ISBN 10: 9780138297053
ISBN 13: 0138297053
Language: EN, FR, DE, ES & NL

Speech Enhancement Book Review:

Speech Enhancement in the STFT Domain

Speech Enhancement in the STFT Domain
Author: Jacob Benesty,Jingdong Chen,Emanuël A.P. Habets
Publsiher: Springer Science & Business Media
Total Pages: 109
Release: 2011-09-18
ISBN 10: 9783642232503
ISBN 13: 3642232507
Language: EN, FR, DE, ES & NL

Speech Enhancement in the STFT Domain Book Review:

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.

Speech Enhancement Modeling and Recognition

Speech Enhancement  Modeling and Recognition
Author: Danel Jaso
Publsiher: Unknown
Total Pages: 280
Release: 2006-09
ISBN 10: 9781681175850
ISBN 13: 1681175851
Language: EN, FR, DE, ES & NL

Speech Enhancement Modeling and Recognition Book Review:

"Communication via speech is one of the essential functions of human beings. Humans possess varied ways to retrieve information from the outside world or to communicate with each other and the three most important sources of information are speech, images and written text. For many purposes, speech stands out as the most efficient and convenient one. Speech not only conveys linguistic contents, but also communicates other useful information like the mood of the speaker. When speaker and listener are near to each other in a quiet environment, communication is generally easy and accurate. However, at a distance or in a noisy background, the listeners ability to understand suffers. Speech enhancement aims to improve speech quality by using various algorithms. The objective of enhancement is improvement in intelligibility and/or overall perceptual quality of degraded speech signal using audio signal processing techniques. Enhancing of speech degraded by noise, or noise reduction, is the most important field of speech enhancement, and used for many applications such as mobile phones, VoIP, teleconferencing systems, speech recognition, and hearing aids. Speech Enhancement, Modeling and Recognition covers important fields in speech processing such as speech enhancement, noise cancellation, multi resolution spectral analysis, voice conversion, speech recognition and emotion recognition from speech in addition to applications. This book will be of immense useful for advanced graduate students, researchers and practicing engineers employed in speech processing."

Speech Enhancement Techniques for Digital Hearing Aids

Speech Enhancement Techniques for Digital Hearing Aids
Author: Komal R. Borisagar,Rohit M. Thanki,Bhavin S. Sedani
Publsiher: Springer
Total Pages: 155
Release: 2018-11-15
ISBN 10: 3319968211
ISBN 13: 9783319968216
Language: EN, FR, DE, ES & NL

Speech Enhancement Techniques for Digital Hearing Aids Book Review:

​This book provides various speech enhancement algorithms for digital hearing aids. It covers information on noise signals extracted from silences of speech signal. The description of the algorithm used for this purpose is also provided. Different types of adaptive filters such as Least Mean Squares (LMS), Normalized LMS (NLMS) and Recursive Lease Squares (RLS) are described for noise reduction in the speech signals. Different types of noises are taken to generate noisy speech signals, and therefore information on various noises signals is provided. The comparative performance of various adaptive filters for noise reduction in speech signals is also described. In addition, the book provides a speech enhancement technique using adaptive filtering and necessary frequency strength enhancement using wavelet transform as per the requirement of audiogram for digital hearing aids. Presents speech enhancement techniques for improving performance of digital hearing aids; Covers various types of adaptive filters and their advantages and limitations; Provides a hybrid speech enhancement technique using wavelet transform and adaptive filters.

A Perspective on Single channel Frequency domain Speech Enhancement

A Perspective on Single channel Frequency domain Speech Enhancement
Author: Jacob Benesty,Yiteng Huang
Publsiher: Morgan & Claypool Publishers
Total Pages: 101
Release: 2011
ISBN 10: 1608456986
ISBN 13: 9781608456987
Language: EN, FR, DE, ES & NL

A Perspective on Single channel Frequency domain Speech Enhancement Book Review:

This book focuses on a class of single-channel noise reduction methods that are performed in the frequency domain via the short-time Fourier transform (STFT). The simplicity and relative effectiveness of this class of approaches make them the dominant choice in practical systems. Even though many popular algorithms have been proposed through more than four decades of continuous research, there are a number of critical areas where our understanding and capabilities still remain quite rudimentary, especially with respect to the relationship between noise reduction and speech distortion. All existing frequency-domain algorithms, no matter how they are developed, have one feature in common: the solution is eventually expressed as a gain function applied to the STFT of the noisy signal only in the current frame. As a result, the narrowband signal-to-noise ratio (SNR) cannot be improved, and any gains achieved in noise reduction on the fullband basis come with a price to pay, which is speech distortion. In this book, we present a new perspective on the problem by exploiting the difference between speech and typical noise in circularity and interframe self-correlation, which were ignored in the past. By gathering the STFT of the microphone signal of the current frame, its complex conjugate, and the STFTs in the previous frames, we construct several new, multiple-observation signal models similar to a microphone array system: there are multiple noisy speech observations, and their speech components are correlated but not completely coherent while their noise components are presumably uncorrelated. Therefore, the multichannel Wiener filter and the minimum variance distortionless response (MVDR) filter that were usually associated with microphone arrays will be developed for single-channel noise reduction in this book. This might instigate a paradigm shift geared toward speech distortionless noise reduction techniques. Table of Contents: Introduction / Problem Formulation / Performance Measures / Linear and Widely Linear Models / Optimal Filters with Model 1 / Optimal Filters with Model 2 / Optimal Filters with Model 3 / Optimal Filters with Model 4 / Experimental Study

The Electrical Engineering Handbook Six Volume Set

The Electrical Engineering Handbook   Six Volume Set
Author: Richard C. Dorf
Publsiher: CRC Press
Total Pages: 3672
Release: 2018-12-14
ISBN 10: 1420049755
ISBN 13: 9781420049756
Language: EN, FR, DE, ES & NL

The Electrical Engineering Handbook Six Volume Set Book Review:

In two editions spanning more than a decade, The Electrical Engineering Handbook stands as the definitive reference to the multidisciplinary field of electrical engineering. Our knowledge continues to grow, and so does the Handbook. For the third edition, it has grown into a set of six books carefully focused on specialized areas or fields of study. Each one represents a concise yet definitive collection of key concepts, models, and equations in its respective domain, thoughtfully gathered for convenient access. Combined, they constitute the most comprehensive, authoritative resource available. Circuits, Signals, and Speech and Image Processing presents all of the basic information related to electric circuits and components, analysis of circuits, the use of the Laplace transform, as well as signal, speech, and image processing using filters and algorithms. It also examines emerging areas such as text to speech synthesis, real-time processing, and embedded signal processing. Electronics, Power Electronics, Optoelectronics, Microwaves, Electromagnetics, and Radar delves into the fields of electronics, integrated circuits, power electronics, optoelectronics, electromagnetics, light waves, and radar, supplying all of the basic information required for a deep understanding of each area. It also devotes a section to electrical effects and devices and explores the emerging fields of microlithography and power electronics. Sensors, Nanoscience, Biomedical Engineering, and Instruments provides thorough coverage of sensors, materials and nanoscience, instruments and measurements, and biomedical systems and devices, including all of the basic information required to thoroughly understand each area. It explores the emerging fields of sensors, nanotechnologies, and biological effects. Broadcasting and Optical Communication Technology explores communications, information theory, and devices, covering all of the basic information needed for a thorough understanding of these areas. It also examines the emerging areas of adaptive estimation and optical communication. Computers, Software Engineering, and Digital Devices examines digital and logical devices, displays, testing, software, and computers, presenting the fundamental concepts needed to ensure a thorough understanding of each field. It treats the emerging fields of programmable logic, hardware description languages, and parallel computing in detail. Systems, Controls, Embedded Systems, Energy, and Machines explores in detail the fields of energy devices, machines, and systems as well as control systems. It provides all of the fundamental concepts needed for thorough, in-depth understanding of each area and devotes special attention to the emerging area of embedded systems. Encompassing the work of the world's foremost experts in their respective specialties, The Electrical Engineering Handbook, Third Edition remains the most convenient, reliable source of information available. This edition features the latest developments, the broadest scope of coverage, and new material on nanotechnologies, fuel cells, embedded systems, and biometrics. The engineering community has relied on the Handbook for more than twelve years, and it will continue to be a platform to launch the next wave of advancements. The Handbook's latest incarnation features a protective slipcase, which helps you stay organized without overwhelming your bookshelf. It is an attractive addition to any collection, and will help keep each volume of the Handbook as fresh as your latest research.

Speech Enhancement

Speech Enhancement
Author: Philipos C. Loizou
Publsiher: CRC Press
Total Pages: 711
Release: 2013-02-25
ISBN 10: 1466504218
ISBN 13: 9781466504219
Language: EN, FR, DE, ES & NL

Speech Enhancement Book Review:

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.

Robust Microphone Array Processing for Speech Enhancement in Hearing Aids

Robust Microphone Array Processing for Speech Enhancement in Hearing Aids
Author: Michael W. Hoffman
Publsiher: Unknown
Total Pages: 394
Release: 1992
ISBN 10:
ISBN 13: MINN:31951D00973784J
Language: EN, FR, DE, ES & NL

Robust Microphone Array Processing for Speech Enhancement in Hearing Aids Book Review:

Metaheuristic Applications to Speech Enhancement

Metaheuristic Applications to Speech Enhancement
Author: Prajna Kunche,K.V.V.S. Reddy
Publsiher: Springer
Total Pages: 122
Release: 2016-04-12
ISBN 10: 3319316834
ISBN 13: 9783319316833
Language: EN, FR, DE, ES & NL

Metaheuristic Applications to Speech Enhancement Book Review:

This book serves as a basic reference for those interested in the application of metaheuristics to speech enhancement. The major goal of the book is to explain the basic concepts of optimization methods and their use in heuristic optimization in speech enhancement to scientists, practicing engineers, and academic researchers in speech processing. The authors discuss why it has been a challenging problem for researchers to develop new enhancement algorithms that aid in the quality and intelligibility of degraded speech. They present powerful optimization methods to speech enhancement that can help to solve the noise reduction problems. Readers will be able to understand the fundamentals of speech processing as well as the optimization techniques, how the speech enhancement algorithms are implemented by utilizing optimization methods, and will be given the tools to develop new algorithms. The authors also provide a comprehensive literature survey regarding the topic.

Experimental Spatial Filtering and Array Calibration for Speech Enhancement

Experimental Spatial Filtering and Array Calibration for Speech Enhancement
Author: Michael John Link
Publsiher: Unknown
Total Pages: 262
Release: 1994
ISBN 10:
ISBN 13: MINN:31951D01071413B
Language: EN, FR, DE, ES & NL

Experimental Spatial Filtering and Array Calibration for Speech Enhancement Book Review:

Speech Enhancement in the Karhunen Lo ve Expansion Domain

Speech Enhancement in the Karhunen Lo  ve Expansion Domain
Author: Jacob Benesty,Jingdong Chen,Yiteng Huang
Publsiher: Morgan & Claypool Publishers
Total Pages: 102
Release: 2011
ISBN 10: 1608456048
ISBN 13: 9781608456048
Language: EN, FR, DE, ES & NL

Speech Enhancement in the Karhunen Lo ve Expansion Domain Book Review:

This book is devoted to the study of the problem of speech enhancement whose objective is the recovery of a signal of interest (i.e., speech) from noisy observations. Typically, the recovery process is accomplished by passing the noisy observations through a linear filter (or a linear transformation). Since both the desired speech and undesired noise are filtered at the same time, the most critical issue of speech enhancement resides in how to design a proper optimal filter that can fully take advantage of the difference between the speech and noise statistics to mitigate the noise effect as much as possible while maintaining the speech perception identical to its original form. The optimal filters can be designed either in the time domain or in a transform space. As the title indicates, this book will focus on developing and analyzing optimal filters in the Karhunen-Loeve expansion (KLE) domain. We begin by describing the basic problem of speech enhancement and the fundamental principles to solve it in the time domain. We then explain how the problem can be equivalently formulated in the KLE domain. Next, we divide the general problem in the KLE domain into four groups, depending on whether interframe and interband information is accounted for, leading to four linear models for speech enhancement in the KLE domain. For each model, we introduce signal processing measures to quantify the performance of speech enhancement, discuss the formation of different cost functions, and address the optimization of these cost functions for the derivation of different optimal filters. Both theoretical analysis and experiments will be provided to study the performance of these filters and the links between the KLE-domain and time-domain optimal filters will be examined. Table of Contents: Introduction / Problem Formulation / Optimal Filters in the Time Domain / Linear Models for Signal Enhancement in the KLE Domain / Optimal Filters in the KLE Domain with Model 1 / Optimal Filters in the KLE Domain with Model 2 / Optimal Filters in the KLE Domain with Model 3 / Optimal Filters in the KLE Domain with Model 4 / Experimental Study"

Speech Enhancement Using Deep Learning

Speech Enhancement Using Deep Learning
Author: Dan Mihai Badescu
Publsiher: Unknown
Total Pages: 329
Release: 2017
ISBN 10:
ISBN 13: OCLC:1120490594
Language: EN, FR, DE, ES & NL

Speech Enhancement Using Deep Learning Book Review:

This thesis explores the possibility to achieve enhancement on noisy speech signals using Deep Neural Networks. Signal enhancement is a classic problem in speech processing. In the last years, researches using deep learning has been used in many speech processing tasks since they have provided very satisfactory results. As a first step, a Signal Analysis Module has been implemented in order to calculate the magnitude and phase of each audio file in the database. The signal is represented into its magnitude and its phase, where the magnitude is modified by the neural network, and then it is reconstructed with the original phase. The implementation of the Neural Networks is divided into two stages.The first stage was the implementation of a Speech Activity Detection Deep Neural Network (SAD-DNN). The magnitude previously calculated, applied to the noisy data, will train the SAD-DNN in order to classify each frame in speech or non-speech. This classification is useful for the network that does the final cleaning. The Speech Activity Detection Deep Neural Network is followed by a Denoising Auto-Encoder (DAE). The magnitude and the label speech or non-speech will be the input of this second Deep Neural Network in charge of denoising the speech signal. The first stage is also optimized to be adequate for the final task in this second stage. In order to do the training, Neural Networks require datasets. In this project the Timit corpus [9] has been used as dataset for the clean voice (target) and the QUT-NOISE TIMIT corpus[4] as noisy dataset (source). Finally, Signal Synthesis Module reconstructs the clean speech signal from the enhanced magnitudes and the phase. In the end, the results provided by the system have been analysed using both objective and subjective measures.

Two Microphone Binary Mask Speech Enhancement in Diffuse and Directional Noise Fields

Two   Microphone Binary Mask Speech Enhancement in Diffuse and Directional Noise Fields
Author: Anonim
Publsiher: Unknown
Total Pages: 329
Release: 2014
ISBN 10:
ISBN 13: OCLC:1051851654
Language: EN, FR, DE, ES & NL

Two Microphone Binary Mask Speech Enhancement in Diffuse and Directional Noise Fields Book Review:

Abstract : Two‐microphone binary mask speech enhancement (2mBMSE) has been of particular interest in recent literature and has shown promising results. Current 2mBMSE systems rely on spatial cues of speech and noise sources. Although these cues are helpful for directional noise sources, they lose their efficiency in diffuse noise fields. We propose a new system that is effective in both directional and diffuse noise conditions. The system exploits two features. The first determines whether a given time–frequency (T‐F) unit of the input spectrum is dominated by a diffuse or directional source. A diffuse signal is certainly a noise signal, but a directional signal could correspond to a noise or speech source. The second feature discriminates between T‐F units dominated by speech or directional noise signals. Speech enhancement is performed using a binary mask, calculated based on the proposed features. In both directional and diffuse noise fields, the proposed system segregates speech T‐F units with hit rates above 85%. It outperforms previous solutions in terms of signal‐to‐noise ratio and perceptual evaluation of speech quality improvement, especially in diffuse noise conditions.