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Neural Text To Speech Synthesis
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Book Synopsis Neural Text-to-Speech Synthesis by : Xu Tan
Download or read book Neural Text-to-Speech Synthesis written by Xu Tan and published by Springer Nature. This book was released on 2023-05-29 with total page 214 pages. Available in PDF, EPUB and Kindle. Book excerpt: 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.
Book Synopsis Text-to-Speech Synthesis by : Paul Taylor
Download or read book Text-to-Speech Synthesis written by Paul Taylor and published by Cambridge University Press. This book was released on 2009-02-19 with total page 626 pages. Available in PDF, EPUB and Kindle. Book excerpt: Text-to-Speech Synthesis provides a complete, end-to-end account of the process of generating speech by computer. Giving an in-depth explanation of all aspects of current speech synthesis technology, it assumes no specialised prior knowledge. Introductory chapters on linguistics, phonetics, signal processing and speech signals lay the foundation, with subsequent material explaining how this knowledge is put to use in building practical systems that generate speech. Including coverage of the very latest techniques such as unit selection, hidden Markov model synthesis, and statistical text analysis, explanations of the more traditional techniques such as format synthesis and synthesis by rule are also provided. Weaving together the various strands of this multidisciplinary field, the book is designed for graduate students in electrical engineering, computer science, and linguistics. It is also an ideal reference for practitioners in the fields of human communication interaction and telephony.
Book Synopsis An Introduction to Text-to-Speech Synthesis by : Thierry Dutoit
Download or read book An Introduction to Text-to-Speech Synthesis written by Thierry Dutoit and published by Springer Science & Business Media. This book was released on 2013-12-01 with total page 306 pages. Available in PDF, EPUB and Kindle. Book excerpt: This is the first book to treat two areas of speech synthesis: natural language processing and the inherent problems it presents for speech synthesis; and digital signal processing, with an emphasis on the concatenative approach. The text guides the reader through the material in a step-by-step easy-to-follow way. The book will be of interest to researchers and students in phonetics and speech communication, in both academia and industry.
Book Synopsis Artificial Neural Networks for Speech Analysis/synthesis by : Mazin G. Rahim
Download or read book Artificial Neural Networks for Speech Analysis/synthesis written by Mazin G. Rahim and published by Kluwer Academic Publishers. This book was released on 1994 with total page 224 pages. Available in PDF, EPUB and Kindle. Book excerpt:
Book Synopsis Speech-to-Speech Translation by : Yutaka Kidawara
Download or read book Speech-to-Speech Translation written by Yutaka Kidawara and published by Springer Nature. This book was released on 2019-11-22 with total page 103 pages. Available in PDF, EPUB and Kindle. Book excerpt: This book provides the readers with retrospective and prospective views with detailed explanations of component technologies, speech recognition, language translation and speech synthesis. Speech-to-speech translation system (S2S) enables to break language barriers, i.e., communicate each other between any pair of person on the glove, which is one of extreme dreams of humankind. People, society, and economy connected by S2S will demonstrate explosive growth without exception. In 1986, Japan initiated basic research of S2S, then the idea spread world-wide and were explored deeply by researchers during three decades. Now, we see S2S application on smartphone/tablet around the world. Computational resources such as processors, memories, wireless communication accelerate this computation-intensive systems and accumulation of digital data of speech and language encourage recent approaches based on machine learning. Through field experiments after long research in laboratories, S2S systems are being well-developed and now ready to utilized in daily life. Unique chapter of this book is end-2-end evaluation by comparing system’s performance and human competence. The effectiveness of the system would be understood by the score of this evaluation. The book will end with one of the next focus of S2S will be technology of simultaneous interpretation for lecture, broadcast news and so on.
Book Synopsis Speech, Hearing and Neural Network Models by : Seiichi Nakagawa
Download or read book Speech, Hearing and Neural Network Models written by Seiichi Nakagawa and published by IOS Press. This book was released on 1995-01-01 with total page 229 pages. Available in PDF, EPUB and Kindle. Book excerpt:
Book Synopsis Predicting Prosody from Text for Text-to-Speech Synthesis by : K. Sreenivasa Rao
Download or read book Predicting Prosody from Text for Text-to-Speech Synthesis written by K. Sreenivasa Rao and published by Springer Science & Business Media. This book was released on 2012-04-27 with total page 136 pages. Available in PDF, EPUB and Kindle. Book excerpt: 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.
Book Synopsis Artificial Neural Network Based Prosody Models for Finnish Text-to-speech Synthesis by : Martti Vainio
Download or read book Artificial Neural Network Based Prosody Models for Finnish Text-to-speech Synthesis written by Martti Vainio and published by . This book was released on 2001 with total page 107 pages. Available in PDF, EPUB and Kindle. Book excerpt:
Book Synopsis Text to Speech Synthesis by : Shrikanth Narayanan
Download or read book Text to Speech Synthesis written by Shrikanth Narayanan and published by Prentice-Hall PTR. This book was released on 2005 with total page 296 pages. Available in PDF, EPUB and Kindle. Book excerpt: 2011 Carol Award winner for Debut Author from ACFW (American Christian Fiction Writers)Jenny Lucas swore she'd never go home again. But being told you're dying has a way of changing things. Years after she left, she and her five-year-old daughter, Isabella, must return to her sleepy North Carolina town to face the ghosts she left behind. They welcome her in the form of her oxygen tank-toting grandmother, her stoic and distant father, and David, Isabella's dad . . . Who doesn't yet know he has a daughter. As Jenny navigates the rough and unknown waters of her new reality, the unforgettable story that unfolds is a testament to the power of love and its ability to change everything-to heal old hurts, bring new beginnings . . . Even overcome the impossible. A stunning debut about love and loss from a talented new voice.
Book Synopsis Intelligent Speech Signal Processing by : Nilanjan Dey
Download or read book Intelligent Speech Signal Processing written by Nilanjan Dey and published by Academic Press. This book was released on 2019-06-15 with total page 210 pages. Available in PDF, EPUB and Kindle. Book excerpt: Intelligent Speech Signal Processing investigates the utilization of speech analytics across several systems and real-world activities, including sharing data analytics related information, creating collaboration networks between several participants, and implementing video-conferencing in different application areas. It provides a forum for readers to discover the characteristics of intelligent speech signal processing systems across different domains. Chapters focus on the latest applications of speech data analysis and management tools across different recording systems. The book emphasizes the multi-disciplinary nature of the field, presenting different applications and challenges with extensive studies on the design, implementation, development, and management of intelligent systems, neural networks, and related machine learning techniques for speech signal processing. Highlights different data analytics techniques in speech signal processing, including machine learning, and data mining Illustrates different applications and challenges across the design, implementation, and management of intelligent systems and neural networks techniques for speech signal processing Includes coverage of biomodal speech recognition, voice activity detection, spoken language and speech disorder identification, automatic speech to speech summarization, and convolutional neural networks
Book Synopsis Supervised Sequence Labelling with Recurrent Neural Networks by : Alex Graves
Download or read book Supervised Sequence Labelling with Recurrent Neural Networks written by Alex Graves and published by Springer. This book was released on 2012-02-06 with total page 148 pages. Available in PDF, EPUB and Kindle. Book excerpt: Supervised sequence labelling is a vital area of machine learning, encompassing tasks such as speech, handwriting and gesture recognition, protein secondary structure prediction and part-of-speech tagging. Recurrent neural networks are powerful sequence learning tools—robust to input noise and distortion, able to exploit long-range contextual information—that would seem ideally suited to such problems. However their role in large-scale sequence labelling systems has so far been auxiliary. The goal of this book is a complete framework for classifying and transcribing sequential data with recurrent neural networks only. Three main innovations are introduced in order to realise this goal. Firstly, the connectionist temporal classification output layer allows the framework to be trained with unsegmented target sequences, such as phoneme-level speech transcriptions; this is in contrast to previous connectionist approaches, which were dependent on error-prone prior segmentation. Secondly, multidimensional recurrent neural networks extend the framework in a natural way to data with more than one spatio-temporal dimension, such as images and videos. Thirdly, the use of hierarchical subsampling makes it feasible to apply the framework to very large or high resolution sequences, such as raw audio or video. Experimental validation is provided by state-of-the-art results in speech and handwriting recognition.
Book Synopsis Data-Driven Techniques in Speech Synthesis by : R.I. Damper
Download or read book Data-Driven Techniques in Speech Synthesis written by R.I. Damper and published by Springer Science & Business Media. This book was released on 2012-12-06 with total page 328 pages. Available in PDF, EPUB and Kindle. Book excerpt: This first review of a new field covers all areas of speech synthesis from text, ranging from text analysis to letter-to-sound conversion. At the leading edge of current research, the concise and accessible book is written by well respected experts in the field.
Book Synopsis Computing and Data Science by : Weijia Cao
Download or read book Computing and Data Science written by Weijia Cao and published by Springer Nature. This book was released on 2022-01-12 with total page 443 pages. Available in PDF, EPUB and Kindle. Book excerpt: This volume constitutes selected papers presented at the Third International Conference on Computing and Data Science, CONF-CDS 2021, held online in August 2021. The 22 full papers 9 short papers presented in this volume were thoroughly reviewed and selected from the 85 qualified submissions. They are organized in topical sections on advances in deep learning; algorithms in machine learning and statistics; advances in natural language processing.
Book Synopsis Multilingual Text-to-Speech Synthesis by : Richard Sproat
Download or read book Multilingual Text-to-Speech Synthesis written by Richard Sproat and published by Springer. This book was released on 1997-10-31 with total page 300 pages. Available in PDF, EPUB and Kindle. Book excerpt: Multilingual Text-to-Speech Synthesis: The Bell Labs Approach is the first monograph-length description of the Bell Labs work on multilingual text-to-speech synthesis. Every important aspect of the system is described, including text analysis, segmental timing, intonation and synthesis. There is also a discussion of evaluation methodologies, as well as a chapter outlining some future areas of research. While the book focuses on the Bell Labs approach to the various problems of converting from text into speech, other approaches are discussed and compared. Thus, this book serves both the function of providing a single reference to an important strand of research in multilingual synthesis, while at the same time providing a source of information on current trends in the field. Chapters in this work were contributed by Richard Sproat, Jan van Santen, Bernd Möbius, Chilin Shih, Joseph Olive, Evelyne Tzoukermann, all of Bell Labs, and Kazuaki Maeda of the University of Pennsylvania.
Book Synopsis Smart Trends in Computing and Communications by : Tomonobu Senjyu
Download or read book Smart Trends in Computing and Communications written by Tomonobu Senjyu and published by Springer Nature. This book was released on with total page 486 pages. Available in PDF, EPUB and Kindle. Book excerpt:
Book Synopsis Text, Speech, and Dialogue by : Elmar Nöth
Download or read book Text, Speech, and Dialogue written by Elmar Nöth and published by Springer Nature. This book was released on with total page 337 pages. Available in PDF, EPUB and Kindle. Book excerpt:
Book Synopsis Unsupervised Learning for Expressive Speech Synthesis by : Igor Jauk
Download or read book Unsupervised Learning for Expressive Speech Synthesis written by Igor Jauk and published by . This book was released on 2018 with total page 142 pages. Available in PDF, EPUB and Kindle. Book excerpt: Nowadays, especially with the upswing of neural networks, speech synthesis is almost totally data driven. The goal of this thesis is to provide methods for automatic and unsupervised learning from data for expressive speech synthesis. In comparison to "ordinary" synthesis systems, it is more difficult to find reliable expressive training data, despite huge availability on sources like Internet. The main difficulty consists in the highly speaker- and situation-dependent nature of expressiveness, causing many and acoustically substantial variations. The consequences are, first, it is very difficult to define labels which reliably identify expressive speech with all nuances. The typical definition of 6 basic emotions, or alike, is a simplification which will have inexcusable consequences dealing with data outside the lab. Second, even if a label set is defined, apart of the enormous manual effort, it is difficult to gain sufficient training data for the models respecting all the nuances and variations. The goal of this thesis is to study automatic training methods for expressive speech synthesis avoiding labeling and to develop applications from these proposals. The focus lies on the acoustic and the semantic domains. For the part of the acoustic domain, the goal is to find suitable acoustic features to represent expressive speech, especially for the multi-speaker domain, as getting closer to real-life uncontrolled data. For this, the perspective will slide away from traditional, mainly prosody-based, features towards features gained with factor analysis, trying to identify the principal components of the expressiveness, namely using i-vectors. Results show that a combination of traditional and i-vector based features performs better in unsupervised clustering of expressive speech than traditional features and even better than large state-of-the-art sets in the multi-speaker domain. Once the feature set is defined, it is used for unsupervised clustering of an audiobook, where from each cluster a voice is trained. Then, the method is evaluated in an audiobook-editing application, where users can use the synthetic voices to create their own dialogues. The obtained results validate the proposal. In this editing application users choose synthetic voices and assign them to the sentences considering the speaking characters and the expressiveness. Involving the semantic domain, this assignment can be achieved automatically, at least partly. Words and sentences are represented numerically in trainable semantic vector spaces, called embeddings, and these can be used to predict the expressiveness to some extent. This method not only permits fully automatic reading of larger text passages, considering the local context, but can also be used as a semantic search engine for training data. Both applications are evaluated in a perceptual test showing the potential of the proposed method. Finally, accounting for the new tendencies in the speech synthesis world, deep neural network based expressive speech synthesis is designed and tested. Emotionally motivated semantic representations of text, sentiment embeddings, trained on the positiveness and the negativeness of movie reviews, are used as an additional input to the system. The neural network now learns not only from segmental and contextual information, but also from the sentiment embeddings, affecting especially prosody. The system is evaluated in two perceptual experiments which show preferences for the inclusion of sentiment embeddings as an additional input.
