Download or read book Audio Source Separation Using Wavenet Architecture with Wavelet Transformed Audio as Input written by Prathmesh Ravindra Matodkar and published by . This book was released on 2019 with total page 0 pages. Available in PDF, EPUB and Kindle. Book excerpt: Audio Source Separation is an interesting problem, which gives us the power to separate individual elements that make up a mixture signal and analyze them or use them or different functions ranging from re mixing, mastering or for educational purpose.With different instruments, sounds, timbers interacting with each other, it is difficult to visualize their combination to make the final mixture signal.There were few methods which attempted exploiting the statistical relations of the individual sources with final the final mixture signals.With the arrival of machine learning, neural networks, researchers are curious to know the outcome of applying various deep learning models for solving this problem of audio source separation. The availability of larger memory and processing power has encouraged the use of deep learning methodologies in solving various problems.Their ability find interesting patterns with the introduction of non linearity, convolutions layers, short memory cells has helped achieve better results in the domains of image, video, audio. These models are flexible, hence a model used in one domain can be modified to suite other domains as well. The development of various APIs like Tensorflow, Keras, Theano, Pytorch has made the realization and application of complicated operations involved in deep learning models easy to understand and implement. A song is made up of different sources, instruments. In this thesis our main focus would be to extract bass, drums and vocals from a given song.These three elemnts have distinct timber and also different frequency regions where they have maximum presence.These sources are also the driving force of a song. Different techniques have been used till date to solve this problem.An overview of these techniques, proposed model and the elements included are explained in the chapters ahead.
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 Audio Source Separation Using Bi directional Gated Recurrent Unit written by Sanjay Majumder and published by . This book was released on 2022 with total page 0 pages. Available in PDF, EPUB and Kindle. Book excerpt: In the world of signal processing, although audio source separation is not a new concept, to date, it has remained a fascinatingly complex task. Because of the vast field of practical application, over the years, researchers from varied backgrounds have deployed advanced and sophisticated algorithms of deep learning, signal processing, data augmentation, and computer listening to isolate individual voices or instruments from the audio mixtures in precision and clarity. Among all these new technologies, neural networks, especially recurrent neural networks (RNN), have promising evidence of optimal results in multimedia problems. However, a series of projects are still going on to give the outcomes more accuracy. This thesis aims to contribute to this field of research by introducing the Bi-directional Gated Recurrent Unit (Bi-GRU) - a newer version of RNN to separate audio stems from the audio mixture in the Time-Frequency domain. The architecture of the GRU is robust yet simple to use compared to its predecessor Long Short Time Memory (LSTM), and most interestingly, it efficiently solves the problem of gradient exploding or gradient vanishing, which could previously result in data over-fitting and under-fitting, respectively. But as information only passes in the forward direction (left to right), both general RNN and GRU suffer from the lack of information from future cells. To resolve this issue, in this study, the bi-directionality feature of RNN has been exploited, which facilitates the accurate learning of the GRU from the previous as well as the future cells, producing a better result. The audio data are transformed into spectrograms, and the Bi-GRU model fetches the essential temporal and spectral information to train and test the system to separate four well-defined audio stems in a supervised manner. This newly developed source separation model is applied on the MUSDB18 [45] dataset to test, and the performance of the model is assessed by using the museval [61] evaluation toolbox and Mean Opinion Score (MOS). The measured performance is then compared with the other known model's performance. In addition, this thesis provides a detailed survey of the audio source separation work, and at the end of this paper, some observations and shortcomings of the system are discussed.
Download or read book Wavelets and Subbands written by Agostino Abbate and published by Springer Science & Business Media. This book was released on 2012-12-06 with total page 562 pages. Available in PDF, EPUB and Kindle. Book excerpt: This book presents connections between the different aspects of wavelet and subband theory.
Download or read book High Performance Computing Systems and Technologies in Scientific Research Automation of Control and Production written by Vladimir Jordan and published by Springer Nature. This book was released on 2022-01-17 with total page 428 pages. Available in PDF, EPUB and Kindle. Book excerpt: This book constitutes selected revised and extended papers from the 11th International Conference on High-Performance Computing Systems and Technologies in Scientific Research, Automation of Control and Production, HPCST 2021, Barnaul, Russia, in May 2021. The 32 full papers presented in this volume were thoroughly reviewed and selected form 98 submissions. The papers are organized in topical sections on Hardware for High-Performance Computing and Signal Processing; Information Technologies and Computer Simulation of Physical Phenomena; Computing Technologies in Discrete Mathematics and Decision Making; Information and Computing Technologies in Automation and Control Science; and Computing Technologies in Information Security Applications.
Download or read book New Era for Robust Speech Recognition written by Shinji Watanabe and published by Springer. This book was released on 2017-10-30 with total page 433 pages. Available in PDF, EPUB and Kindle. Book excerpt: 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.
Download or read book Developing Virtual Synthesizers with VCV Rack written by Leonardo Gabrielli and published by CRC Press. This book was released on 2020-02-07 with total page 287 pages. Available in PDF, EPUB and Kindle. Book excerpt: Developing Virtual Synthesizers with VCV Rack takes the reader step by step through the process of developing synthesizer modules, beginning with the elementary and leading up to more engaging examples. Using the intuitive VCV Rack and its open-source C++ API, this book will guide even the most inexperienced reader to master efficient DSP coding to create oscillators, filters, and complex modules. Examining practical topics related to releasing plugins and managing complex graphical user interaction, with an intuitive study of signal processing theory specifically tailored for sound synthesis and virtual analog, this book covers everything from theory to practice. With exercises and example patches in each chapter, the reader will build a library of synthesizer modules that they can modify and expand. Supplemented by a companion website, this book is recommended reading for undergraduate and postgraduate students of audio engineering, music technology, computer science, electronics, and related courses; audio coding and do-it-yourself enthusiasts; and professionals looking for a quick guide to VCV Rack. VCV Rack is a free and open-source software available online.
Download or read book Machine Learning and Artificial Intelligence in Geosciences written by and published by Academic Press. This book was released on 2020-09-22 with total page 318 pages. Available in PDF, EPUB and Kindle. Book excerpt: Advances in Geophysics, Volume 61 - Machine Learning and Artificial Intelligence in Geosciences, the latest release in this highly-respected publication in the field of geophysics, contains new chapters on a variety of topics, including a historical review on the development of machine learning, machine learning to investigate fault rupture on various scales, a review on machine learning techniques to describe fractured media, signal augmentation to improve the generalization of deep neural networks, deep generator priors for Bayesian seismic inversion, as well as a review on homogenization for seismology, and more. - Provides high-level reviews of the latest innovations in geophysics - Written by recognized experts in the field - Presents an essential publication for researchers in all fields of geophysics
Download or read book Speech Enhancement written by Shoji Makino and published by Springer Science & Business Media. This book was released on 2005-03-17 with total page 432 pages. Available in PDF, EPUB and Kindle. Book excerpt: We live in a noisy world! In all applications (telecommunications, hands-free communications, recording, human-machine interfaces, etc) that require at least one microphone, the signal of interest is usually contaminated by noise and reverberation. As a result, the microphone signal has to be "cleaned" with digital signal processing tools before it is played out, transmitted, or stored. This book is about speech enhancement. Different well-known and state-of-the-art methods for noise reduction, with one or multiple microphones, are discussed. By speech enhancement, we mean not only noise reduction but also dereverberation and separation of independent signals. These topics are also covered in this book. However, the general emphasis is on noise reduction because of the large number of applications that can benefit from this technology. The goal of this book is to provide a strong reference for researchers, engineers, and graduate students who are interested in the problem of signal and speech enhancement. To do so, we invited well-known experts to contribute chapters covering the state of the art in this focused field.
Download or read book Audio Source Separation written by Shoji Makino and published by Springer. This book was released on 2018-03-01 with total page 389 pages. Available in PDF, EPUB and Kindle. Book excerpt: This book provides the first comprehensive overview of the fascinating topic of audio source separation based on non-negative matrix factorization, deep neural networks, and sparse component analysis. The first section of the book covers single channel source separation based on non-negative matrix factorization (NMF). After an introduction to the technique, two further chapters describe separation of known sources using non-negative spectrogram factorization, and temporal NMF models. In section two, NMF methods are extended to multi-channel source separation. Section three introduces deep neural network (DNN) techniques, with chapters on multichannel and single channel separation, and a further chapter on DNN based mask estimation for monaural speech separation. In section four, sparse component analysis (SCA) is discussed, with chapters on source separation using audio directional statistics modelling, multi-microphone MMSE-based techniques and diffusion map methods. The book brings together leading researchers to provide tutorial-like and in-depth treatments on major audio source separation topics, with the objective of becoming the definitive source for a comprehensive, authoritative, and accessible treatment. This book is written for graduate students and researchers who are interested in audio source separation techniques based on NMF, DNN and SCA.
Download or read book Neural Approaches to Dynamics of Signal Exchanges written by Anna Esposito and published by Springer Nature. This book was released on 2019-09-18 with total page 525 pages. Available in PDF, EPUB and Kindle. Book excerpt: The book presents research that contributes to the development of intelligent dialog systems to simplify diverse aspects of everyday life, such as medical diagnosis and entertainment. Covering major thematic areas: machine learning and artificial neural networks; algorithms and models; and social and biometric data for applications in human–computer interfaces, it discusses processing of audio-visual signals for the detection of user-perceived states, the latest scientific discoveries in processing verbal (lexicon, syntax, and pragmatics), auditory (voice, intonation, vocal expressions) and visual signals (gestures, body language, facial expressions), as well as algorithms for detecting communication disorders, remote health-status monitoring, sentiment and affect analysis, social behaviors and engagement. Further, it examines neural and machine learning algorithms for the implementation of advanced telecommunication systems, communication with people with special needs, emotion modulation by computer contents, advanced sensors for tracking changes in real-life and automatic systems, as well as the development of advanced human–computer interfaces. The book does not focus on solving a particular problem, but instead describes the results of research that has positive effects in different fields and applications.
Download or read book Cybernetics Cognition and Machine Learning Applications written by Vinit Kumar Gunjan and published by Springer Nature. This book was released on 2021-03-30 with total page 439 pages. Available in PDF, EPUB and Kindle. Book excerpt: This book includes the original, peer reviewed research articles from the 2nd International Conference on Cybernetics, Cognition and Machine Learning Applications (ICCCMLA 2020), held in August, 2020 at Goa, India. It covers the latest research trends or developments in areas of data science, artificial intelligence, neural networks, cognitive science and machine learning applications, cyber physical systems and cybernetics.
Download or read book Machine Learning for Medical Image Reconstruction written by Florian Knoll and published by Springer Nature. This book was released on 2019-10-24 with total page 274 pages. Available in PDF, EPUB and Kindle. Book excerpt: This book constitutes the refereed proceedings of the Second International Workshop on Machine Learning for Medical Reconstruction, MLMIR 2019, held in conjunction with MICCAI 2019, in Shenzhen, China, in October 2019. The 24 full papers presented were carefully reviewed and selected from 32 submissions. The papers are organized in the following topical sections: deep learning for magnetic resonance imaging; deep learning for computed tomography; and deep learning for general image reconstruction.
Download or read book Handbook of Biometric Anti Spoofing written by Sébastien Marcel and published by Springer. This book was released on 2019-01-01 with total page 522 pages. Available in PDF, EPUB and Kindle. Book excerpt: This authoritative and comprehensive handbook is the definitive work on the current state of the art of Biometric Presentation Attack Detection (PAD) – also known as Biometric Anti-Spoofing. Building on the success of the previous, pioneering edition, this thoroughly updated second edition has been considerably expanded to provide even greater coverage of PAD methods, spanning biometrics systems based on face, fingerprint, iris, voice, vein, and signature recognition. New material is also included on major PAD competitions, important databases for research, and on the impact of recent international legislation. Valuable insights are supplied by a selection of leading experts in the field, complete with results from reproducible research, supported by source code and further information available at an associated website. Topics and features: reviews the latest developments in PAD for fingerprint biometrics, covering optical coherence tomography (OCT) technology, and issues of interoperability; examines methods for PAD in iris recognition systems, and the application of stimulated pupillary light reflex for this purpose; discusses advancements in PAD methods for face recognition-based biometrics, such as research on 3D facial masks and remote photoplethysmography (rPPG); presents a survey of PAD for automatic speaker recognition (ASV), including the use of convolutional neural networks (CNNs), and an overview of relevant databases; describes the results yielded by key competitions on fingerprint liveness detection, iris liveness detection, and software-based face anti-spoofing; provides analyses of PAD in fingervein recognition, online handwritten signature verification, and in biometric technologies on mobile devicesincludes coverage of international standards, the E.U. PSDII and GDPR directives, and on different perspectives on presentation attack evaluation. This text/reference is essential reading for anyone involved in biometric identity verification, be they students, researchers, practitioners, engineers, or technology consultants. Those new to the field will also benefit from a number of introductory chapters, outlining the basics for the most important biometrics.
Download or read book Machine Audition Principles Algorithms and Systems written by Wang, Wenwu and published by IGI Global. This book was released on 2010-07-31 with total page 554 pages. Available in PDF, EPUB and Kindle. Book excerpt: Machine audition is the study of algorithms and systems for the automatic analysis and understanding of sound by machine. It has recently attracted increasing interest within several research communities, such as signal processing, machine learning, auditory modeling, perception and cognition, psychology, pattern recognition, and artificial intelligence. However, the developments made so far are fragmented within these disciplines, lacking connections and incurring potentially overlapping research activities in this subject area. Machine Audition: Principles, Algorithms and Systems contains advances in algorithmic developments, theoretical frameworks, and experimental research findings. This book is useful for professionals who want an improved understanding about how to design algorithms for performing automatic analysis of audio signals, construct a computing system for understanding sound, and learn how to build advanced human-computer interactive systems.
Download or read book Emerging Technology in Modelling and Graphics written by Jyotsna Kumar Mandal and published by Springer. This book was released on 2019-07-16 with total page 799 pages. Available in PDF, EPUB and Kindle. Book excerpt: The book covers cutting-edge and advanced research in modelling and graphics. Gathering high-quality papers presented at the First International Conference on Emerging Technology in Modelling and Graphics, held from 6 to 8 September 2018 in Kolkata, India, it addresses topics including: image processing and analysis, image segmentation, digital geometry for computer imaging, image and security, biometrics, video processing, medical imaging, and virtual and augmented reality.
Download or read book An Intuitive Exploration of Artificial Intelligence written by Simant Dube and published by Springer Nature. This book was released on 2021-06-21 with total page 355 pages. Available in PDF, EPUB and Kindle. Book excerpt: This book develops a conceptual understanding of Artificial Intelligence (AI), Deep Learning and Machine Learning in the truest sense of the word. It is an earnest endeavor to unravel what is happening at the algorithmic level, to grasp how applications are being built and to show the long adventurous road in the future. An Intuitive Exploration of Artificial Intelligence offers insightful details on how AI works and solves problems in computer vision, natural language understanding, speech understanding, reinforcement learning and synthesis of new content. From the classic problem of recognizing cats and dogs, to building autonomous vehicles, to translating text into another language, to automatically converting speech into text and back to speech, to generating neural art, to playing games, and the author's own experience in building solutions in industry, this book is about explaining how exactly the myriad applications of AI flow out of its immense potential. The book is intended to serve as a textbook for graduate and senior-level undergraduate courses in AI. Moreover, since the book provides a strong geometrical intuition about advanced mathematical foundations of AI, practitioners and researchers will equally benefit from the book.
