Download or read book Speech Enhancement Using Training based Non negative Matrix Factorization Techniques written by Hanwook Chung and published by . This book was released on 2018 with total page pages. Available in PDF, EPUB and Kindle. Book excerpt: "In this thesis, we develop novel training-based non-negative matrix factorization (NMF) algorithms for single and multi-channel speech enhancement.After introducing the problem and reviewing background material, we first present a regularized NMF algorithm with Gaussian mixtures and masking model for single-channel speech enhancement. The proposed framework seeks to exploit the statistical properties of the clean speech and noise. This is accomplished by including the log-likelihood functions (LLF) of the clean speech and noise magnitude spectra, based on Gaussian mixture models (GMM), as the regularization terms in the NMF cost function. Moreover, we incorporate the masking effects of the human auditory system to further improve the enhanced speech quality.Second, we introduce a training and compensation algorithm of the class-conditioned NMF model for single-channel speech enhancement. The main goal is to reduce the residual noise components that have features similar to the speech. To this end, during the training stage, the basis vectors of different sources are obtained in a way that prevents them from representing each other, based on the concept of classification. Another goal is to handle the mismatch between the characteristics of the training and test data. This is accomplished by employing extra free basis vectors during the enhancement stage to capture the features which are not included in the training data.Finally, we present a novel multi-channel speech enhancement algorithm based on a Bayesian NMF model. Essentially, we consider the Poisson-distributed latent variable model for multi-channel NMF. During the training stage, the NMF parameters are estimated from the tensor-based training data. During the enhancement stage, the clean speech signal is estimated via the NMF-based minimum variance distortionless response (MVDR) beamforming technique. To this end, the source locations are estimated by observing the spatial output power of a delay-and-sum (DS) beamformer applied to the NMF-based pre-processed noisy speech signal.For each one of the above algorithms, objective experiments are carried out for different combinations of speaker, noise types and signal-to-noise ratio. The results show that the proposed methods provide better speech enhancement performance than the selected benchmark algorithms under considered test conditions." --

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.

Download or read book Non negative Matrix Factorization Techniques written by Ganesh R. Naik and published by Springer. This book was released on 2015-09-25 with total page 200 pages. Available in PDF, EPUB and Kindle. Book excerpt: This book collects new results, concepts and further developments of NMF. The open problems discussed include, e.g. in bioinformatics: NMF and its extensions applied to gene expression, sequence analysis, the functional characterization of genes, clustering and text mining etc. The research results previously scattered in different scientific journals and conference proceedings are methodically collected and presented in a unified form. While readers can read the book chapters sequentially, each chapter is also self-contained. This book can be a good reference work for researchers and engineers interested in NMF, and can also be used as a handbook for students and professionals seeking to gain a better understanding of the latest applications of NMF.

Download or read book Speech Enhancement Using an Iterative Posterior NMF written by Sunnydayal Vanambathina and published by . This book was released on 2020 with total page 0 pages. Available in PDF, EPUB and Kindle. Book excerpt: Over the years, miscellaneous methods for speech enhancement have been proposed, such as spectral subtraction (SS) and minimum mean square error (MMSE) estimators. These methods do not require any prior knowledge about the speech and noise signals nor any training stage beforehand, so they are highly flexible and allow implementation in various situations. However, these algorithms usually assume that the noise is stationary and are thus not good at dealing with nonstationary noise types, especially under low signal-to-noise (SNR) conditions. To overcome the drawbacks of the above methods, nonnegative matrix factorization (NMF) is introduced. NMF approach is more robust to nonstationary noise. In this chapter, we are actually interested in the application of speech enhancement using NMF approach. A speech enhancement method based on regularized nonnegative matrix factorization (NMF) for nonstationary Gaussian noise is proposed. The spectral components of speech and noise are modeled as Gamma and Rayleigh, respectively. We propose to adaptively estimate the sufficient statistics of these distributions to obtain a natural regularization of the NMF criterion.

Download or read book Speech Enhancement Using Nonnegative Matrix Factorization and Hidden Markov Models written by and published by . This book was released on 2013 with total page 52 pages. Available in PDF, EPUB and Kindle. Book excerpt:

Download or read book Speech and Computer written by Andrey Ronzhin and published by Springer. This book was released on 2014-10-10 with total page 497 pages. Available in PDF, EPUB and Kindle. Book excerpt: This book constitutes the refereed proceedings of the 16th International Conference on Speech and Computer, SPECOM 2014, held in Novi Sad, Serbia. The 56 revised full papers presented together with 3 invited talks were carefully reviewed and selected from 100 initial submissions. It is a conference with long tradition that attracts researchers in the area of computer speech processing (recognition, synthesis, understanding etc.) and related domains (including signal processing, language and text processing, multi-modal speech processing or human-computer interaction for instance).

Download or read book Advances in Multimedia Information Processing PCM 2016 written by Enqing Chen and published by Springer. This book was released on 2016-11-26 with total page 762 pages. Available in PDF, EPUB and Kindle. Book excerpt: The two-volume proceedings LNCS 9916 and 9917, constitute the proceedings of the 17th Pacific-Rim Conference on Multimedia, PCM 2016, held in Xi`an, China, in September 2016. The total of 128 papers presented in these proceedings was carefully reviewed and selected from 202 submissions. The focus of the conference was as follows in multimedia content analysis, multimedia signal processing and communications, and multimedia applications and services.

Download or read book Speech Enhancement Using a Reduced Complexity MFCC based Deep Neural Network written by Ryan Razani and published by . This book was released on 2018 with total page pages. Available in PDF, EPUB and Kindle. Book excerpt: "In contrast to classical noise reduction methods introduced over the past decades, this work focuses on a regression-based single-channel speech enhancement framework using DNN, as recently introduced by Liu et al.. While the latter framework can lead to improved speech quality compared to classical approaches, it is afflicted by high computational complexity in the training stage. The main contribution of this work is to reduce the DNN complexity by introducing a spectral feature mapping from noisy mel frequency cepstral coefficients (MFCC) to enhanced short time Fourier transform (STFT) spectrum. Leveraging MFCC not only has the advantage of mimicking the logarithmic perception of human auditory system, but this approach requires much fewer input features and consequently lead to reduced DNN complexity. Exploiting the frequency domain speech features obtained from the results of such a mapping also avoids the information loss in reconstructing the time-domain speech signal from its MFCC. While the proposed method aims to predict clean speech spectra from corrupted speech inputs, its performance is further improved by incorporating information about the noise environment into the training phase. We implemented the proposed DNN method with different numbers of MFCC and used it to enhance several different types of noisy speech files. Experimental results of perceptual evaluation of speech quality (PESQ) show that the proposed approach can outperform the benchmark algorithms including a recently proposed non-negative matrix factorization (NMF) approach, and this for various speakers and noise types, and different SNR levels. More importantly, the proposed approach with MFCC leads to a significant reduction in complexity, where the runtime is reduced by a factor of approximately five." --

Download or read book Proceedings of the International Conference on Advanced Intelligent Systems and Informatics 2020 written by Aboul Ella Hassanien and published by Springer Nature. This book was released on 2020-09-19 with total page 893 pages. Available in PDF, EPUB and Kindle. Book excerpt: This book presents the proceedings of the 6th International Conference on Advanced Intelligent Systems and Informatics 2020 (AISI2020), which took place in Cairo, Egypt, from October 19 to 21, 2020. This international and interdisciplinary conference, which highlighted essential research and developments in the fields of informatics and intelligent systems, was organized by the Scientific Research Group in Egypt (SRGE). The book is divided into several sections, covering the following topics: Intelligent Systems, Deep Learning Technology, Document and Sentiment Analysis, Blockchain and Cyber Physical System, Health Informatics and AI against COVID-19, Data Mining, Power and Control Systems, Business Intelligence, Social Media and Digital Transformation, Robotic, Control Design, and Smart Systems.

Download or read book Fundamentals of Music Processing written by Meinard Müller and published by Springer. This book was released on 2015-07-21 with total page 509 pages. Available in PDF, EPUB and Kindle. Book excerpt: 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.

Download or read book Nonnegative Matrix and Tensor Factorizations written by Andrzej Cichocki and published by John Wiley & Sons. This book was released on 2009-07-10 with total page 500 pages. Available in PDF, EPUB and Kindle. Book excerpt: This book provides a broad survey of models and efficient algorithms for Nonnegative Matrix Factorization (NMF). This includes NMF’s various extensions and modifications, especially Nonnegative Tensor Factorizations (NTF) and Nonnegative Tucker Decompositions (NTD). NMF/NTF and their extensions are increasingly used as tools in signal and image processing, and data analysis, having garnered interest due to their capability to provide new insights and relevant information about the complex latent relationships in experimental data sets. It is suggested that NMF can provide meaningful components with physical interpretations; for example, in bioinformatics, NMF and its extensions have been successfully applied to gene expression, sequence analysis, the functional characterization of genes, clustering and text mining. As such, the authors focus on the algorithms that are most useful in practice, looking at the fastest, most robust, and suitable for large-scale models. Key features: Acts as a single source reference guide to NMF, collating information that is widely dispersed in current literature, including the authors’ own recently developed techniques in the subject area. Uses generalized cost functions such as Bregman, Alpha and Beta divergences, to present practical implementations of several types of robust algorithms, in particular Multiplicative, Alternating Least Squares, Projected Gradient and Quasi Newton algorithms. Provides a comparative analysis of the different methods in order to identify approximation error and complexity. Includes pseudo codes and optimized MATLAB source codes for almost all algorithms presented in the book. The increasing interest in nonnegative matrix and tensor factorizations, as well as decompositions and sparse representation of data, will ensure that this book is essential reading for engineers, scientists, researchers, industry practitioners and graduate students across signal and image processing; neuroscience; data mining and data analysis; computer science; bioinformatics; speech processing; biomedical engineering; and multimedia.

Download or read book Artificial Intelligence written by Jude Hemanth and published by Springer. This book was released on 2019-07-04 with total page 335 pages. Available in PDF, EPUB and Kindle. Book excerpt: This book constitutes the refereed proceedings of the Second International Conference, SLAAI-ICAI 2018, held in Moratuwa, Sri Lanka, in December 2018. The 32 revised full papers presented were carefully reviewed and selected from numerous submissions. The papers are organized in the following topical sections: ​intelligence systems; neural networks; game theory; ontology engineering; natural language processing; agent based system; signal and image processing.

Download or read book Matrix and Tensor Factorization Techniques for Recommender Systems written by Panagiotis Symeonidis and published by Springer. This book was released on 2017-01-29 with total page 101 pages. Available in PDF, EPUB and Kindle. Book excerpt: This book presents the algorithms used to provide recommendations by exploiting matrix factorization and tensor decomposition techniques. It highlights well-known decomposition methods for recommender systems, such as Singular Value Decomposition (SVD), UV-decomposition, Non-negative Matrix Factorization (NMF), etc. and describes in detail the pros and cons of each method for matrices and tensors. This book provides a detailed theoretical mathematical background of matrix/tensor factorization techniques and a step-by-step analysis of each method on the basis of an integrated toy example that runs throughout all its chapters and helps the reader to understand the key differences among methods. It also contains two chapters, where different matrix and tensor methods are compared experimentally on real data sets, such as Epinions, GeoSocialRec, Last.fm, BibSonomy, etc. and provides further insights into the advantages and disadvantages of each method. The book offers a rich blend of theory and practice, making it suitable for students, researchers and practitioners interested in both recommenders and factorization methods. Lecturers can also use it for classes on data mining, recommender systems and dimensionality reduction methods.

Download or read book Active Learning written by Sílvio Manuel Brito and published by BoD – Books on Demand. This book was released on 2019-10-02 with total page 164 pages. Available in PDF, EPUB and Kindle. Book excerpt: Active learning is now a form of learning that accompanies the knowledge evolution that challenges the learner to promote it, but also encourages him to investigate and become emotionally involved in the task. The great key to obtaining this behavior successfully depends, therefore, on the subject's involvement and ability to undertake, so that active learning becomes emotional entrepreneurial learning that generates new ideas and new forms of knowledge. From memorization, we move on to inquiry, from questioning to constructive participation, from hypostasis to problem-solving, from generalization to critical thinking. When we look at this book, we see real examples, concrete, and senses, from the most important act of human nature: learning!

Download or read book Latent Variable Analysis and Signal Separation written by Fabian Theis and published by Springer. This book was released on 2012-02-09 with total page 552 pages. Available in PDF, EPUB and Kindle. Book excerpt: This book constitutes the proceedings of the 10th International Conference on Latent Variable Analysis and Signal Separation, LVA/ICA 2012, held in Tel Aviv, Israel, in March 2012. The 20 revised full papers presented together with 42 revised poster papers, 1 keynote lecture, and 2 overview papers for the regular, as well as for the special session were carefully reviewed and selected from numerous submissions. Topics addressed are ranging from theoretical issues such as causality analysis and measures, through novel methods for employing the well-established concepts of sparsity and non-negativity for matrix and tensor factorization, down to a variety of related applications ranging from audio and biomedical signals to precipitation analysis.

Download or read book Advances in Natural Computation Fuzzy Systems and Knowledge Discovery written by Hongying Meng and published by Springer Nature. This book was released on 2021-06-26 with total page 1925 pages. Available in PDF, EPUB and Kindle. Book excerpt: 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.

Download or read book Machine Learning Methods with Noisy Incomplete or Small Datasets written by Jordi Solé-Casals and published by MDPI. This book was released on 2021-08-17 with total page 316 pages. Available in PDF, EPUB and Kindle. Book excerpt: Over the past years, businesses have had to tackle the issues caused by numerous forces from political, technological and societal environment. The changes in the global market and increasing uncertainty require us to focus on disruptive innovations and to investigate this phenomenon from different perspectives. The benefits of innovations are related to lower costs, improved efficiency, reduced risk, and better response to the customers’ needs due to new products, services or processes. On the other hand, new business models expose various risks, such as cyber risks, operational risks, regulatory risks, and others. Therefore, we believe that the entrepreneurial behavior and global mindset of decision-makers significantly contribute to the development of innovations, which benefit by closing the prevailing gap between developed and developing countries. Thus, this Special Issue contributes to closing the research gap in the literature by providing a platform for a scientific debate on innovation, internationalization and entrepreneurship, which would facilitate improving the resilience of businesses to future disruptions. Order Your Print Copy