Single Channel Speech Enhancement Based On Deep Neural Networks

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Single Channel Speech Enhancement Based On Deep Neural Networks

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Author : Zhiheng Ouyang
language : en
Publisher:
Release Date : 2020

Single Channel Speech Enhancement Based On Deep Neural Networks written by Zhiheng Ouyang and has been published by this book supported file pdf, txt, epub, kindle and other format this book has been release on 2020 with categories.

Speech enhancement (SE) aims to improve the speech quality of the degraded speech. Recently, researchers have resorted to deep-learning as a primary tool for speech enhancement, which often features deterministic models adopting supervised training. Typically, a neural network is trained as a mapping function to convert some features of noisy speech to certain targets that can be used to reconstruct clean speech. These methods of speech enhancement using neural networks have been focused on the estimation of spectral magnitude of clean speech considering that estimating spectral phase with neural networks is difficult due to the wrapping effect. As an alternative, complex spectrum estimation implicitly resolves the phase estimation problem and has been proven to outperform spectral magnitude estimation. In the first contribution of this thesis, a fully convolutional neural network (FCN) is proposed for complex spectrogram estimation. Stacked frequency-dilated convolution is employed to obtain an exponential growth of the receptive field in frequency domain. The proposed network also features an efficient implementation that requires much fewer parameters as compared with conventional deep neural network (DNN) and convolutional neural network (CNN) while still yielding a comparable performance. Consider that speech enhancement is only useful in noisy conditions, yet conventional SE methods often do not adapt to different noisy conditions. In the second contribution, we proposed a model that provides an automatic "on/off" switch for speech enhancement. It is capable of scaling its computational complexity under different signal-to-noise ratio (SNR) levels by detecting clean or near-clean speech which requires no processing. By adopting information maximizing generative adversarial network (InfoGAN) in a deterministic, supervised manner, we incorporate the functionality of SNR-indicator into the model that adds little additional cost to the system. We evaluate the proposed SE methods with two objectives: speech intelligibility and application to automatic speech recognition (ASR). Experimental results have shown that the CNN-based model is applicable for both objectives while the InfoGAN-based model is more useful in terms of speech intelligibility. The experiments also show that SE for ASR may be more challenging than improving the speech intelligibility, where a series of factors, including training dataset and neural network models, would impact the ASR performance.

Speech Signal Processing Based On Deep Learning In Complex Acoustic Environments

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Author : Xiao-Lei Zhang
language : en
Publisher: Elsevier
Release Date : 2024-09-04

Speech Signal Processing Based On Deep Learning In Complex Acoustic Environments written by Xiao-Lei Zhang and has been published by Elsevier this book supported file pdf, txt, epub, kindle and other format this book has been release on 2024-09-04 with Computers categories.

Speech Signal Processing Based on Deep Learning in Complex Acoustic Environments provides a detailed discussion of deep learning-based robust speech processing and its applications. The book begins by looking at the basics of deep learning and common deep network models, followed by front-end algorithms for deep learning-based speech denoising, speech detection, single-channel speech enhancement multi-channel speech enhancement, multi-speaker speech separation, and the applications of deep learning-based speech denoising in speaker verification and speech recognition. - Provides a comprehensive introduction to the development of deep learning-based robust speech processing - Covers speech detection, speech enhancement, dereverberation, multi-speaker speech separation, robust speaker verification, and robust speech recognition - Focuses on a historical overview and then covers methods that demonstrate outstanding performance in practical applications

Audio Source Separation And Speech Enhancement

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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.

Iccce 2021

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Author : Amit Kumar
language : en
Publisher: Springer Nature
Release Date : 2022-05-15

Iccce 2021 written by Amit Kumar and has been published by Springer Nature this book supported file pdf, txt, epub, kindle and other format this book has been release on 2022-05-15 with Technology & Engineering categories.

This book is a collection of research articles presented at the 4th International Conference on Communications and Cyber-Physical Engineering (ICCCE 2021), held on April 9 and 10, 2021, at CMR Engineering College, Hyderabad, India. ICCCE is one of the most prestigious conferences conceptualized in the field of networking and communication technology offering in-depth information on the latest developments in voice, data, image, and multimedia. Discussing the latest developments in voice and data communication engineering, cyber-physical systems, network science, communication software, image, and multimedia processing research and applications, as well as communication technologies and other related technologies, it includes contributions from both academia and industry. This book is a valuable resource for scientists, research scholars, and PG students working to formulate their research ideas and find the future directions in these areas. Further, it may serve as a reference work to understand the latest engineering and technologies used by practicing engineers in the field of communication engineering.

Advances In Natural Computation Fuzzy Systems And Knowledge Discovery

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Author : Hongying Meng
language : en
Publisher: Springer Nature
Release Date : 2021-06-26

Advances In Natural Computation Fuzzy Systems And Knowledge Discovery written by Hongying Meng and has been published by Springer Nature this book supported file pdf, txt, epub, kindle and other format this book has been release on 2021-06-26 with Technology & Engineering categories.

This book consists of papers on the recent progresses in the state of the art in natural computation, fuzzy systems and knowledge discovery. The book is useful for researchers, including professors, graduate students, as well as R & D staff in the industry, with a general interest in natural computation, fuzzy systems and knowledge discovery. The work printed in this book was presented at the 2020 16th International Conference on Natural Computation, Fuzzy Systems and Knowledge Discovery (ICNC-FSKD 2020), held in Xi'an, China, from 19 to 21 December 2020. All papers were rigorously peer-reviewed by experts in the areas.

Digital Speech Transmission And Enhancement

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Author : Peter Vary
language : en
Publisher: John Wiley & Sons
Release Date : 2023-11-29

Digital Speech Transmission And Enhancement written by Peter Vary 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 2023-11-29 with Technology & Engineering categories.

DIGITAL SPEECH TRANSMISSION AND ENHANCEMENT Enables readers to understand the latest developments in speech enhancement/transmission due to advances in computational power and device miniaturization The Second Edition of Digital Speech Transmission and Enhancement has been updated throughout to provide all the necessary details on the latest advances in the theory and practice in speech signal processing and its applications, including many new research results, standards, algorithms, and developments which have recently appeared and are on their way into state-of-the-art applications. Besides mobile communications, which constituted the main application domain of the first edition, speech enhancement for hearing instruments and man-machine interfaces has gained significantly more prominence in the past decade, and as such receives greater focus in this updated and expanded second edition. Readers can expect to find information and novel methods on: Low-latency spectral analysis-synthesis, single-channel and dual-channel algorithms for noise reduction and dereverberation Multi-microphone processing methods, which are now widely used in applications such as mobile phones, hearing aids, and man-computer interfaces Algorithms for near-end listening enhancement, which provide a significantly increased speech intelligibility for users at the noisy receiving side of their mobile phone Fundamentals of speech signal processing, estimation and machine learning, speech coding, error concealment by soft decoding, and artificial bandwidth extension of speech signals Digital Speech Transmission and Enhancement is a single-source, comprehensive guide to the fundamental issues, algorithms, standards, and trends in speech signal processing and speech communication technology, and as such is an invaluable resource for engineers, researchers, academics, and graduate students in the areas of communications, electrical engineering, and information technology.

Proceedings Of International Conference On Power Electronics And Renewable Energy Systems

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Author : C. Subramani
language : en
Publisher: Springer Nature
Release Date : 2021-11-21

Proceedings Of International Conference On Power Electronics And Renewable Energy Systems written by C. Subramani and has been published by Springer Nature this book supported file pdf, txt, epub, kindle and other format this book has been release on 2021-11-21 with Technology & Engineering categories.

This book features selected papers from the International Conference on Power Electronics and Renewable Energy Systems (ICPERES 2021), organized by SRM Institute of Science and Technology, Chennai, India, during April 2021. It covers recent advances in the field of soft computing applications in power systems, power system modeling and control, power system stability, power quality issues and solutions, smart grid, green and renewable energy technology optimization techniques in electrical systems, power electronics controllers for power systems, power converters and modeling, high voltage engineering, networking grid and cloud computing, computer architecture and embedded systems, fuzzy logic control, fuzzy decision support systems, and control systems. The book presents innovative work by leading academics, researchers, and experts from industry.

Deep Neural Network Approach For Single Channel Speech Enhancement Processing

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Author : Dongfu Li
language : en
Publisher:
Release Date : 2016

Deep Neural Network Approach For Single Channel Speech Enhancement Processing written by Dongfu Li 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.

Speech intelligibility represents how comprehensible a speech is. It is more important than speech quality in some applications. Single channel speech intelligibility enhancement is much more difficult than multi-channel intelligibility enhancement. It has recently been reported that training-based single channel speech intelligibility enhancement algorithms perform better than Signal to Noise Ratio (SNR) based algorithm. In this thesis, a training-based Deep Neural Network (DNN) is used to improve single channel speech intelligibility. To increase the performance of the DNN, the Multi-Resolution Cochlea Gram (MRCG) feature set is used as the input of the DNN. MATLAB objective test results show that the MRCG-DNN approach is more robust than a Gaussian Mixture Model (GMM) approach. The MRCG-DNN also works better than other DNN training algorithms. Various conditions such as different speakers, different noise conditions and reverberation were tested in the thesis.

International Conference On Intelligent Computing And Applications

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Author : M. Arun Bhaskar
language : en
Publisher: Springer
Release Date : 2018-09-08

International Conference On Intelligent Computing And Applications written by M. Arun Bhaskar and has been published by Springer this book supported file pdf, txt, epub, kindle and other format this book has been release on 2018-09-08 with Technology & Engineering categories.

The book is a collection of best papers presented at the International Conference on Intelligent Computing and Applications (ICICA 2018), held at Velammal Engineering College, Chennai, India on 2–3 February 2018. Presenting original work in the field of computational intelligence and power and computing technology, it focuses on soft computing applications in power systems; power-system modeling and control; FACTS devices – applications in power systems; power-system stability and switchgear and protection; power quality issues and solutions; smart grids; green and renewable energy technologies; optimization techniques in electrical systems; power electronics controllers for power systems; power converters and modeling; high voltage engineering; diagnosis and sensing systems; and robotics.

New Era For Robust Speech Recognition

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Author : Shinji Watanabe
language : en
Publisher: Springer
Release Date : 2017-10-30

New Era For Robust Speech Recognition written by Shinji Watanabe and has been published by Springer this book supported file pdf, txt, epub, kindle and other format this book has been release on 2017-10-30 with Computers categories.

This book covers the state-of-the-art in deep neural-network-based methods for noise robustness in distant speech recognition applications. It provides insights and detailed descriptions of some of the new concepts and key technologies in the field, including novel architectures for speech enhancement, microphone arrays, robust features, acoustic model adaptation, training data augmentation, and training criteria. The contributed chapters also include descriptions of real-world applications, benchmark tools and datasets widely used in the field. This book is intended for researchers and practitioners working in the field of speech processing and recognition who are interested in the latest deep learning techniques for noise robustness. It will also be of interest to graduate students in electrical engineering or computer science, who will find it a useful guide to this field of research.