Reinforcement Learning for Dialogue Systems Optimization with User Adaptation - read free eBook in online reader or directly download on the web page. Select files or add your book in reader. Download and read online ebook Reinforcement Learning for Dialogue Systems Optimization with User Adaptation write by Nicolas Carrara. This book was released on 2019. Reinforcement Learning for Dialogue Systems Optimization with User Adaptation available in PDF, EPUB and Kindle.
Data-Driven Methods for Adaptive Spoken Dialogue Systems
Data-Driven Methods for Adaptive Spoken Dialogue Systems - read free eBook in online reader or directly download on the web page. Select files or add your book in reader. Download and read online ebook Data-Driven Methods for Adaptive Spoken Dialogue Systems write by Oliver Lemon. This book was released on 2012-10-21. Data-Driven Methods for Adaptive Spoken Dialogue Systems available in PDF, EPUB and Kindle. Data driven methods have long been used in Automatic Speech Recognition (ASR) and Text-To-Speech (TTS) synthesis and have more recently been introduced for dialogue management, spoken language understanding, and Natural Language Generation. Machine learning is now present “end-to-end” in Spoken Dialogue Systems (SDS). However, these techniques require data collection and annotation campaigns, which can be time-consuming and expensive, as well as dataset expansion by simulation. In this book, we provide an overview of the current state of the field and of recent advances, with a specific focus on adaptivity.
Reinforcement Learning for Adaptive Dialogue Systems
Reinforcement Learning for Adaptive Dialogue Systems - read free eBook in online reader or directly download on the web page. Select files or add your book in reader. Download and read online ebook Reinforcement Learning for Adaptive Dialogue Systems write by Verena Rieser. This book was released on 2011-11-23. Reinforcement Learning for Adaptive Dialogue Systems available in PDF, EPUB and Kindle. The past decade has seen a revolution in the field of spoken dialogue systems. As in other areas of Computer Science and Artificial Intelligence, data-driven methods are now being used to drive new methodologies for system development and evaluation. This book is a unique contribution to that ongoing change. A new methodology for developing spoken dialogue systems is described in detail. The journey starts and ends with human behaviour in interaction, and explores methods for learning from the data, for building simulation environments for training and testing systems, and for evaluating the results. The detailed material covers: Spoken and Multimodal dialogue systems, Wizard-of-Oz data collection, User Simulation methods, Reinforcement Learning, and Evaluation methodologies. The book is a research guide for students and researchers with a background in Computer Science, AI, or Machine Learning. It navigates through a detailed case study in data-driven methods for development and evaluation of spoken dialogue systems. Common challenges associated with this approach are discussed and example solutions are provided. This work provides insights, lessons, and inspiration for future research and development – not only for spoken dialogue systems in particular, but for data-driven approaches to human-machine interaction in general.
Data-Driven Methods for Adaptive Spoken Dialogue Systems
Data-Driven Methods for Adaptive Spoken Dialogue Systems - read free eBook in online reader or directly download on the web page. Select files or add your book in reader. Download and read online ebook Data-Driven Methods for Adaptive Spoken Dialogue Systems write by Oliver Lemon. This book was released on 2012-10-20. Data-Driven Methods for Adaptive Spoken Dialogue Systems available in PDF, EPUB and Kindle. Data driven methods have long been used in Automatic Speech Recognition (ASR) and Text-To-Speech (TTS) synthesis and have more recently been introduced for dialogue management, spoken language understanding, and Natural Language Generation. Machine learning is now present “end-to-end” in Spoken Dialogue Systems (SDS). However, these techniques require data collection and annotation campaigns, which can be time-consuming and expensive, as well as dataset expansion by simulation. In this book, we provide an overview of the current state of the field and of recent advances, with a specific focus on adaptivity.
Neural Approaches to Conversational AI: Question Answering, Task-Oriented Dialogues and Social Chatbots
Neural Approaches to Conversational AI: Question Answering, Task-Oriented Dialogues and Social Chatbots - read free eBook in online reader or directly download on the web page. Select files or add your book in reader. Download and read online ebook Neural Approaches to Conversational AI: Question Answering, Task-Oriented Dialogues and Social Chatbots write by Jianfeng Gao. This book was released on 2019-02-21. Neural Approaches to Conversational AI: Question Answering, Task-Oriented Dialogues and Social Chatbots available in PDF, EPUB and Kindle. This monograph is the first survey of neural approaches to conversational AI that targets Natural Language Processing and Information Retrieval audiences. It provides a comprehensive survey of the neural approaches to conversational AI that have been developed in the last few years, covering QA, task-oriented and social bots with a unified view of optimal decision making.The authors draw connections between modern neural approaches and traditional approaches, allowing readers to better understand why and how the research has evolved and to shed light on how they can move forward. They also present state-of-the-art approaches to training dialogue agents using both supervised and reinforcement learning. Finally, the authors sketch out the landscape of conversational systems developed in the research community and released in industry, demonstrating via case studies the progress that has been made and the challenges that are still being faced.Neural Approaches to Conversational AI is a valuable resource for students, researchers, and software developers. It provides a unified view, as well as a detailed presentation of the important ideas and insights needed to understand and create modern dialogue agents that will be instrumental to making world knowledge and services accessible to millions of users in ways that seem natural and intuitive.
