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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.
This book constitutes the refereed proceedings of the 13th International Conference on Computational Processing of the Portuguese Language, PROPOR 2018, held in Canela, RS, Brazil, in September 2018. The 42 full papers, 3 short papers and 4 other papers presented in this volume were carefully reviewed and selected from 92 submissions. The papers are organized in topical sections named: Corpus Linguistics, Information Extraction, LanguageApplications, Language Resources, Sentiment Analysis and Opinion Mining, Speech Processing, and Syntax and Parsing.
This book constitutes the proceedings of the First International Workshop on Machine Learning for Multimodal Healthcare Date, ML4MHD 2023, held in Honolulu, Hawaii, USA, in July 2023. The 18 full papers presented were carefully reviewed and selected from 30 submissions. The workshop's primary objective was to bring together experts from diverse fields such as medicine, pathology, biology, and machine learning. With the aim to present novel methods and solutions that address healthcare challenges, especially those that arise from the complexity and heterogeneity of patient data.
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.
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. TOC:Introduction.- Study of the Wiener Filter for Noise Reduction.- Statistical Methods for the Enhancement of Noisy Speech.- Single- und Multi-Microphone Spectral Amplitude Estimation Using a Super-Gaussian Speech Model.- From Volatility Modeling of Financial Time-Series to Stochastic Modeling and Enhancement of Speech Signals.- Single-Microphone Noise Suppression for 3G Handsets Based on Weighted Noise Estimation.- Signal Subspace Techniques for Speech Enhancement.- Speech Enhancement: Application of the Kalman Filter in the Estimate-Maximize (EM) Framework.- Speech Distortion Weighted Multichannel Wiener Filtering Techniques for Noise Reduction.- Adpative Microphone Arrays Employing Spatial Quadratic Soft Constraints and Spectral Shaping.- Single-Microphone Blind Dereverberation.- Separation and Dereverberation of Speech Signals with Multiple Microphones.- Frequency-Domain Blind Source Separation.- Subband Based Blind Source Separation.- Real-Time Blind Source Separation for Moving Speech Signals.- Separation of Speech by Computational Auditory Scene Analysis
The book constitutes proceedings of the International Conference on Intelligent Systems and Human-Machine Collaboration 2022. The papers consist of research from different domains of human-machine interaction, computer engineering like quantum computational intelligence, big data analytics, the Internet of things, etc. The book includes significant contributions from academia and industry dealing with human-machine interaction both from the theoretical development and the application point of view. It also brings out research articles in interdisciplinary platforms applying human-machine interaction. The book is useful to researchers and practitioners alike.
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.
This book presents a collection of papers from the Spring 1995 Work shop on Computational Approaches to Processing the Prosody of Spon taneous Speech, hosted by the ATR Interpreting Telecommunications Re search Laboratories in Kyoto, Japan. The workshop brought together lead ing researchers in the fields of speech and signal processing, electrical en gineering, psychology, and linguistics, to discuss aspects of spontaneous speech prosody and to suggest approaches to its computational analysis and modelling. The book is divided into four sections. Part I gives an overview and theoretical background to the nature of spontaneous speech, differentiating it from the lab-speech that has been the focus of so many earlier analyses. Part II focuses on the prosodic features of discourse and the structure of the spoken message, Part ilIon the generation and modelling of prosody for computer speech synthesis. Part IV discusses how prosodic information can be used in the context of automatic speech recognition. Each section of the book starts with an invited overview paper to situate the chapters in the context of current research. We feel that this collection of papers offers interesting insights into the scope and nature of the problems concerned with the computational analysis and modelling of real spontaneous speech, and expect that these works will not only form the basis of further developments in each field but also merge to form an integrated computational model of prosody for a better understanding of human processing of the complex interactions of the speech chain.