Speech Hearing And Neural Network Models

Author : Seiichi Nakagawa,Kiyohiro Shikano,Yoh'ichi Tohkura
Publisher : IOS Press
Page : 254 pages
File Size : 50,6 Mb
Release : 1995
Category : Medical
ISBN : 9051991789

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Speech, Hearing and Neural Network Models by Seiichi Nakagawa,Kiyohiro Shikano,Yoh'ichi Tohkura Pdf

A wide range of fields of study support speech research. They cover many fields like for instance phonetics, linguistics, psychology, cognitive science, sonics, information engineering (information theory, pattern recognition, artificial intelligence), and it is an extremely difficult job to carry all of these in one body.The first half of this book gives detailed descriptions of engineering applications, that is the speech, hearing and perception mechanisms that form the basis for automatic synthesis and recognition of speech. The second half of this book gives a detailed explanation of speech synthesis and recognition based on a collective physiological approach, that is the artificial neural networks which imitate human neural networks and have once again been bathed in attention lately. The characteristics of this book are that, along with having engineers and technicians as its main targets, it explains engineering models based on speech science.

Author : Gerard Chollet,Maria-Gabriella Di Benedetto,Anna Esposito,Maria Marinaro
Publisher : Springer Science & Business Media
Page : 352 pages
File Size : 42,9 Mb
Release : 2012-12-06
Category : Technology & Engineering
ISBN : 9781447108450

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Speech Processing, Recognition and Artificial Neural Networks by Gerard Chollet,Maria-Gabriella Di Benedetto,Anna Esposito,Maria Marinaro Pdf

Speech Processing, Recognition and Artificial Neural Networks contains papers from leading researchers and selected students, discussing the experiments, theories and perspectives of acoustic phonetics as well as the latest techniques in the field of spe ech science and technology. Topics covered in this book include; Fundamentals of Speech Analysis and Perceptron; Speech Processing; Stochastic Models for Speech; Auditory and Neural Network Models for Speech; Task-Oriented Applications of Automatic Speech Recognition and Synthesis.

Author : Yoshua Bengio
Publisher : London ; Toronto : International Thomson Computer Press
Page : 184 pages
File Size : 40,5 Mb
Release : 1996
Category : Computers
ISBN : UOM:39015038446848

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Neural Networks for Speech and Sequence Recognition by Yoshua Bengio Pdf

Sequence recognition is a crucial element in many applications in the fields of speech analysis, control, and modeling. This book applies the techniques of neural networks and hidden Markov models to the problems of sequence recognition, and as such will prove valuable to researchers and graduate students alike.

Author : Bernd J. Kröger,Trevor Bekolay
Publisher : Springer
Page : 280 pages
File Size : 53,9 Mb
Release : 2019-07-11
Category : Medical
ISBN : 9783030158538

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Neural Modeling of Speech Processing and Speech Learning by Bernd J. Kröger,Trevor Bekolay Pdf

This book explores the processes of spoken language production and perception from a neurobiological perspective. After presenting the basics of speech processing and speech acquisition, a neurobiologically-inspired and computer-implemented neural model is described, which simulates the neural processes of speech processing and speech acquisition. This book is an introduction to the field and aimed at students and scientists in neuroscience, computer science, medicine, psychology and linguistics.

Author : Gerard Chollet,Anna Esposito,Marcos Faundez-Zanuy,Maria Marinaro
Publisher : Springer
Page : 438 pages
File Size : 48,9 Mb
Release : 2005-07-12
Category : Computers
ISBN : 9783540318866

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Nonlinear Speech Modeling and Applications by Gerard Chollet,Anna Esposito,Marcos Faundez-Zanuy,Maria Marinaro Pdf

This book presents the revised tutorial lectures given at the International Summer School on Nonlinear Speech Processing-Algorithms and Analysis held in Vietri sul Mare, Salerno, Italy in September 2004. The 14 revised tutorial lectures by leading international researchers are organized in topical sections on dealing with nonlinearities in speech signals, acoustic-to-articulatory modeling of speech phenomena, data driven and speech processing algorithms, and algorithms and models based on speech perception mechanisms. Besides the tutorial lectures, 15 revised reviewed papers are included presenting original research results on task oriented speech applications.

Author : Xu Tan
Publisher : Springer Nature
Page : 214 pages
File Size : 44,8 Mb
Release : 2023-05-29
Category : Computers
ISBN : 9789819908271

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Neural Text-to-Speech Synthesis by Xu Tan Pdf

Text-to-speech (TTS) aims to synthesize intelligible and natural speech based on the given text. It is a hot topic in language, speech, and machine learning research and has broad applications in industry. This book introduces neural network-based TTS in the era of deep learning, aiming to provide a good understanding of neural TTS, current research and applications, and the future research trend. This book first introduces the history of TTS technologies and overviews neural TTS, and provides preliminary knowledge on language and speech processing, neural networks and deep learning, and deep generative models. It then introduces neural TTS from the perspective of key components (text analyses, acoustic models, vocoders, and end-to-end models) and advanced topics (expressive and controllable, robust, model-efficient, and data-efficient TTS). It also points some future research directions and collects some resources related to TTS. This book is the first to introduce neural TTS in a comprehensive and easy-to-understand way and can serve both academic researchers and industry practitioners working on TTS.

Author : Ivan Habernal,Vaclav Matousek
Publisher : Springer
Page : 601 pages
File Size : 49,6 Mb
Release : 2013-08-17
Category : Computers
ISBN : 9783642405853

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Text, Speech, and Dialogue by Ivan Habernal,Vaclav Matousek Pdf

This book constitutes the refereed proceedings of the 16th International Conference on Text, Speech and Dialogue, TSD 2013, held in Pilsen, Czech Republic, in September 2013. The 65 papers presented together with 5 invited talks were carefully reviewed and selected from 148 submissions. The main topics of this year's conference was corpora, texts and transcription, speech analysis, recognition and synthesis, and their intertwining within NL dialogue systems. The topics also included speech recognition, corpora and language resources, speech and spoken language generation, tagging, classification and parsing of text and speech, semantic processing of text and speech, integrating applications of text and speech processing, as well as automatic dialogue systems, and multimodal techniques and modelling.

Author : Yoav Goldberg
Publisher : Morgan & Claypool Publishers
Page : 401 pages
File Size : 51,9 Mb
Release : 2017-04-17
Category : Computers
ISBN : 9781681731551

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Neural Network Methods in Natural Language Processing by Yoav Goldberg Pdf

Neural networks are a family of powerful machine learning models and this book focuses on their application to natural language data. The first half of the book (Parts I and II) covers the basics of supervised machine learning and feed-forward neural networks, the basics of working with machine learning over language data, and the use of vector-based rather than symbolic representations for words. It also covers the computation-graph abstraction, which allows to easily define and train arbitrary neural networks, and is the basis behind the design of contemporary neural network software libraries. The second part of the book (Parts III and IV) introduces more specialized neural network architectures, including 1D convolutional neural networks, recurrent neural networks, conditioned-generation models, and attention-based models. These architectures and techniques are the driving force behind state-of-the-art algorithms for machine translation, syntactic parsing, and many other applications. Finally, we also discuss tree-shaped networks, structured prediction, and the prospects of multi-task learning.

Author : Dong Yu,Li Deng
Publisher : Springer
Page : 321 pages
File Size : 42,7 Mb
Release : 2014-11-11
Category : Technology & Engineering
ISBN : 9781447157793

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Automatic Speech Recognition by Dong Yu,Li Deng Pdf

This book provides a comprehensive overview of the recent advancement in the field of automatic speech recognition with a focus on deep learning models including deep neural networks and many of their variants. This is the first automatic speech recognition book dedicated to the deep learning approach. In addition to the rigorous mathematical treatment of the subject, the book also presents insights and theoretical foundation of a series of highly successful deep learning models.

Author : Shigeru Katagiri
Publisher : Artech House Publishers
Page : 560 pages
File Size : 43,7 Mb
Release : 2000
Category : Computers
ISBN : UOM:39015049972048

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Handbook of Neural Networks for Speech Processing by Shigeru Katagiri Pdf

Here are the comprehensive details on cutting edge technologies employing neural networks for speech recognition and speech processing in modern communications. Going far beyond the simple speech recognition technologies on the market today, this new book, written by and for speech and signal processing engineers in industry, R&D, and academia, takes you to the forefront of the hottest emergent neural net-based speech processing techniques.

Author : Hervé A. Bourlard,Nelson Morgan
Publisher : Springer Science & Business Media
Page : 329 pages
File Size : 47,6 Mb
Release : 2012-12-06
Category : Technology & Engineering
ISBN : 9781461532101

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Connectionist Speech Recognition by Hervé A. Bourlard,Nelson Morgan Pdf

Connectionist Speech Recognition: A Hybrid Approach describes the theory and implementation of a method to incorporate neural network approaches into state of the art continuous speech recognition systems based on hidden Markov models (HMMs) to improve their performance. In this framework, neural networks (and in particular, multilayer perceptrons or MLPs) have been restricted to well-defined subtasks of the whole system, i.e. HMM emission probability estimation and feature extraction. The book describes a successful five-year international collaboration between the authors. The lessons learned form a case study that demonstrates how hybrid systems can be developed to combine neural networks with more traditional statistical approaches. The book illustrates both the advantages and limitations of neural networks in the framework of a statistical systems. Using standard databases and comparison with some conventional approaches, it is shown that MLP probability estimation can improve recognition performance. Other approaches are discussed, though there is no such unequivocal experimental result for these methods. Connectionist Speech Recognition is of use to anyone intending to use neural networks for speech recognition or within the framework provided by an existing successful statistical approach. This includes research and development groups working in the field of speech recognition, both with standard and neural network approaches, as well as other pattern recognition and/or neural network researchers. The book is also suitable as a text for advanced courses on neural networks or speech processing.

Author : Anonim
Publisher : Unknown
Page : 126 pages
File Size : 55,6 Mb
Release : 1992
Category : Research
ISBN : UIUC:30112105167875

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Scientific Information Bulletin by Anonim Pdf

Author : Uday Kamath,John Liu,James Whitaker
Publisher : Springer
Page : 621 pages
File Size : 44,7 Mb
Release : 2019-06-10
Category : Computers
ISBN : 9783030145965

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Deep Learning for NLP and Speech Recognition by Uday Kamath,John Liu,James Whitaker Pdf

This textbook explains Deep Learning Architecture, with applications to various NLP Tasks, including Document Classification, Machine Translation, Language Modeling, and Speech Recognition. With the widespread adoption of deep learning, natural language processing (NLP),and speech applications in many areas (including Finance, Healthcare, and Government) there is a growing need for one comprehensive resource that maps deep learning techniques to NLP and speech and provides insights into using the tools and libraries for real-world applications. Deep Learning for NLP and Speech Recognition explains recent deep learning methods applicable to NLP and speech, provides state-of-the-art approaches, and offers real-world case studies with code to provide hands-on experience. Many books focus on deep learning theory or deep learning for NLP-specific tasks while others are cookbooks for tools and libraries, but the constant flux of new algorithms, tools, frameworks, and libraries in a rapidly evolving landscape means that there are few available texts that offer the material in this book. The book is organized into three parts, aligning to different groups of readers and their expertise. The three parts are: Machine Learning, NLP, and Speech Introduction The first part has three chapters that introduce readers to the fields of NLP, speech recognition, deep learning and machine learning with basic theory and hands-on case studies using Python-based tools and libraries. Deep Learning Basics The five chapters in the second part introduce deep learning and various topics that are crucial for speech and text processing, including word embeddings, convolutional neural networks, recurrent neural networks and speech recognition basics. Theory, practical tips, state-of-the-art methods, experimentations and analysis in using the methods discussed in theory on real-world tasks. Advanced Deep Learning Techniques for Text and Speech The third part has five chapters that discuss the latest and cutting-edge research in the areas of deep learning that intersect with NLP and speech. Topics including attention mechanisms, memory augmented networks, transfer learning, multi-task learning, domain adaptation, reinforcement learning, and end-to-end deep learning for speech recognition are covered using case studies.

Author : K. Sreenivasa Rao
Publisher : Springer Science & Business Media
Page : 136 pages
File Size : 46,9 Mb
Release : 2012-04-27
Category : Technology & Engineering
ISBN : 9781461413387

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Predicting Prosody from Text for Text-to-Speech Synthesis by K. Sreenivasa Rao Pdf

Predicting Prosody from Text for Text-to-Speech Synthesis covers the specific aspects of prosody, mainly focusing on how to predict the prosodic information from linguistic text, and then how to exploit the predicted prosodic knowledge for various speech applications. Author K. Sreenivasa Rao discusses proposed methods along with state-of-the-art techniques for the acquisition and incorporation of prosodic knowledge for developing speech systems. Positional, contextual and phonological features are proposed for representing the linguistic and production constraints of the sound units present in the text. This book is intended for graduate students and researchers working in the area of speech processing.

Author : Adam Gadomski,Sylwia Zielińska-Raczyńska
Publisher : MDPI
Page : 166 pages
File Size : 45,6 Mb
Release : 2021-01-20
Category : Technology & Engineering
ISBN : 9783039367467

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Condensed-Matter-Principia Based Information & Statistical Measures by Adam Gadomski,Sylwia Zielińska-Raczyńska Pdf

This book summarizes the efforts of ten papers collected by the Special Issue "Condensed-Matter-Principia Based Information & Statistical Measures: From Classical to Quantum". It calls for papers which deal with condensed-matter systems, or their interdisciplinary analogs, for which well-defined classical–statistical vs. quantum information measures can be inferred while based on the entropy concept. The contents have mainly been rested upon objectives addressed by an international colloquium held on October 2019, in UTP Bydgoszcz, Poland (see http://zmpf.imif.utp.edu.pl/rci-jcs/rci-jcs-4/), with an emphasis placed on the achievements of Professor Gerard Czajkowski, who commenced his research activity with open diffusion–reaction systems under the supervision of Roman S. Ingarden (Toruń), a father of Polish synergetics, and original thermodynamic approaches to self-organization. The active cooperation of Professor Czajkowski, mainly with German physicists (Friedrich Schloegl, Aachen; Werner Ebeling, Berlin), ought to be highlighted. In light of this, a development of his research, as it has moved from statistical thermodynamics to solid state theory, pursued in terms of nonlinear solid-state optics (Franco Bassani, Pisa), and culminated very recently with large quasiparticles termed Rydberg excitons, and their coherent interactions with light, is worth delineating.