Natural Language Dialog Systems and Intelligent Assistants


Book Description

This book covers state-of-the-art topics on the practical implementation of Spoken Dialog Systems and intelligent assistants in everyday applications. It presents scientific achievements in language processing that result in the development of successful applications and addresses general issues regarding the advances in Spoken Dialog Systems with applications in robotics, knowledge access and communication. Emphasis is placed on the following topics: speaker/language recognition, user modeling / simulation, evaluation of dialog system, multi-modality / emotion recognition from speech, speech data mining, language resource and databases, machine learning for spoken dialog systems and educational and healthcare applications.




Spoken Natural Language Dialog Systems


Book Description

As spoken natural language dialog systems technology continues to make great strides, numerous issues regarding dialog processing still need to be resolved. This book presents an exciting new dialog processing architecture that allows for a number of behaviors required for effective human-machine interactions, including: problem-solving to help the user carry out a task, coherent subdialog movement during the problem-solving process, user model usage, expectation usage for contextual interpretation and error correction, and variable initiative behavior for interacting with users of differing expertise. The book also details how different dialog problems in processing can be handled simultaneously, and provides instructions and in-depth result from pertinent experiments. Researchers and professionals in natural language systems will find this important new book an invaluable addition to their libraries.




Hybrid Artificial Intelligent Systems


Book Description

This volume constitutes the refereed proceedings of the 12th International Conference on Hybrid Artificial Intelligent Systems, HAIS 2017, held in La Rioja, Spain, in June 2017. The 60 full papers published in this volume were carefully reviewed and selected from 130 submissions. They are organized in the following topical sections: data mining, knowledge discovery and big data; bioinspired models and evolutionary computing; learning algorithms; visual analysis and advanced data processing techniques; data mining applications; and hybrid intelligent applications.




Advances in Knowledge Discovery and Data Mining


Book Description

The 4-volume set LNAI 13935 - 13938 constitutes the proceedings of the 27th Pacific-Asia Conference on Knowledge Discovery and Data Mining, PAKDD 2023, which took place in Osaka, Japan during May 25–28, 2023. The 143 papers presented in these proceedings were carefully reviewed and selected from 813 submissions. They deal with new ideas, original research results, and practical development experiences from all KDD related areas, including data mining, data warehousing, machine learning, artificial intelligence, databases, statistics, knowledge engineering, big data technologies, and foundations.




Conversational AI


Book Description

This book provides a comprehensive introduction to Conversational AI. While the idea of interacting with a computer using voice or text goes back a long way, it is only in recent years that this idea has become a reality with the emergence of digital personal assistants, smart speakers, and chatbots. Advances in AI, particularly in deep learning, along with the availability of massive computing power and vast amounts of data, have led to a new generation of dialogue systems and conversational interfaces. Current research in Conversational AI focuses mainly on the application of machine learning and statistical data-driven approaches to the development of dialogue systems. However, it is important to be aware of previous achievements in dialogue technology and to consider to what extent they might be relevant to current research and development. Three main approaches to the development of dialogue systems are reviewed: rule-based systems that are handcrafted using best practice guidelines; statistical data-driven systems based on machine learning; and neural dialogue systems based on end-to-end learning. Evaluating the performance and usability of dialogue systems has become an important topic in its own right, and a variety of evaluation metrics and frameworks are described. Finally, a number of challenges for future research are considered, including: multimodality in dialogue systems, visual dialogue; data efficient dialogue model learning; using knowledge graphs; discourse and dialogue phenomena; hybrid approaches to dialogue systems development; dialogue with social robots and in the Internet of Things; and social and ethical issues.




Increasing Naturalness and Flexibility in Spoken Dialogue Interaction


Book Description

This book compiles and presents a synopsis on current global research efforts to push forward the state of the art in dialogue technologies, including advances to language and context understanding, and dialogue management, as well as human–robot interaction, conversational agents, question answering and lifelong learning for dialogue systems.




Advances in Practical Applications of Scalable Multi-agent Systems. The PAAMS Collection


Book Description

This book constitutes the refereed proceedings of the 14th International Conference on Practical Applications of Scalable Multi-agent Systems, PAAMS 2016, held in Sevilla, Spain, in June 2016. The 9 revised full papers, 10 short papers, and 16 Demo papers were carefully reviewed and selected from 58 submissions (39 full paper and 19 Demo paper submissions. The papers report on the application and validation of agent-based models, methods, and technologies in a number of key application areas, including day life and real world, energy and networks, human and trust, markets and bids, models and tools, negotiation and conversation, scalability and resources.




Conversational AI


Book Description

Design, develop, and deploy human-like AI solutions that chat with your customers, solve their problems, and streamline your support services. In Conversational AI, you will learn how to: Pick the right AI assistant type and channel for your needs Write dialog with intentional tone and specificity Train your AI’s classifier from the ground up Create question-and-direct-response AI assistants Design and optimize a process flow for web and voice Test your assistant’s accuracy and plan out improvements Conversational AI: Chatbots that work teaches you to create the kind of AI-enabled assistants that are revolutionizing the customer service industry. You’ll learn to build effective conversational AI that can automate common inquiries and easily address your customers' most common problems. This engaging and entertaining book delivers the essential technical and creative skills for designing successful AI solutions, from coding process flows and training machine learning, to improving your written dialog. Purchase of the print book includes a free eBook in PDF, Kindle, and ePub formats from Manning Publications. About the technology Create AI-driven chatbots and other intelligent agents that humans actually enjoy talking to! Adding intelligence to automated response systems saves time and money for you and your customers. Conversational AI systems excel at routine tasks such as answering common questions, classifying issues, and routing customers to the appropriate human staff. This book will show you how to build effective, production-ready AI assistants. About the book Conversational AI is a guide to creating AI-driven voice and text agents for customer support and other conversational tasks. This practical and entertaining book combines design theory with techniques for building and training AI systems. In it, you’ll learn how to find training data, assess performance, and write dialog that sounds human. You’ll go from building simple chatbots to designing the voice assistant for a complete call center. What's inside Pick the right AI for your needs Train your AI classifier Create question-and-direct-response assistants Design and optimize a process flow About the reader For software developers. Examples use Watson Assistant and Python. About the author Andrew R. Freed is a Master Inventor and Senior Technical Staff Member at IBM. He has worked in AI solutions since 2012. Table of Contents PART 1 FOUNDATIONS 1 Introduction to conversational AI 2 Building your first conversational AI PART 2 DESIGNING FOR SUCCESS 3 Designing effective processes 4 Designing effective dialogue 5 Building a successful AI assistant PART 3 TRAINING AND TESTING 6 Training your assistant 7 How accurate is your assistant? 8 Testing your dialogue flows PART 4 MAINTENANCE 9 Deployment and management 10 Improving your assistant PART 5 ADVANCED/OPTIONAL TOPICS 11 Building your own classifier 12 Additional training for voice assistants




Electronic Governance and Open Society: Challenges in Eurasia


Book Description

This book constitutes the refereed proceedings of the 7th Conference on Electronic Governance and Open Society: Challenges in Eurasia, EGOSE 2020, held in St. Petersburg, Russia, in November 2020. The 35 full papers and 5 short papers were carefully reviewed and selected from 59 submissions. The papers are organized in topical sections on ​digital government: services, policies, laws, practices, surveillance; digital society: openness, participation, trust, competences; digital data: data science, methods, modelling, AI, NLP.




Advanced Social Interaction with Agents


Book Description

This book presents lectures given at the 8th International Workshop on Spoken Dialog Systems. As agents evolve in terms of their ability to carry on a dialog with users, several qualities are emerging as essential components of a successful system. Users do not carry on long conversations on only one topic—they tend to switch between several topics. Thus the authors are observing the emergence of multi-domain systems that enable users to seamlessly hop from one domain to another. The systems have become active social partners. Accordingly, work on social dialog has become crucial to active and engaging human–robot/agent interaction. These new systems call for a coherent framework that guides their actions as chatbots and conversational agents. Human–Robot/Agent assessment mechanisms naturally lend themselves to this task. As these systems increasingly assist humans in a multitude of tasks, the ethics of their existence, their design and their interaction with users are becoming crucial issues. This book discusses the essential players and features involved, such as chat-based agents, multi-domain dialog systems, human–robot interaction, social dialog policy, and advanced dialog system architectures.