Oliver Lemon – författare

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6 produkter

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6 produkter

Data-Driven Methods for Adaptive Spoken Dialogue Systems
Computational Learning for Conversational Interfaces
AvOliver Lemon,Olivier Pietquin
Inbunden, Engelska, 2012
1 118 kr
Skickas inom 10-15 vardagar
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.
Data-Driven Methods for Adaptive Spoken Dialogue Systems
Computational Learning for Conversational Interfaces
AvOlivier Pietquin,Oliver Lemon
E-bok
PDF, Engelska, 2012
1 413 kr
Läs direkt efter köp
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.
Data-Driven Methods for Adaptive Spoken Dialogue Systems
Computational Learning for Conversational Interfaces
AvOliver Lemon,Olivier Pietquin
Häftad, Engelska, 2014
1 086 kr
Skickas inom 10-15 vardagar
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
A Data-driven Methodology for Dialogue Management and Natural Language Generation
AvVerena Rieser,Oliver Lemon
Inbunden, Engelska, 2011
1 118 kr
Skickas inom 10-15 vardagar
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.
Reinforcement Learning for Adaptive Dialogue Systems
A Data-driven Methodology for Dialogue Management and Natural Language Generation
AvOliver Lemon,Verena Rieser
E-bok
PDF, Engelska, 2011
1 459 kr
Läs direkt efter köp
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.
Reinforcement Learning for Adaptive Dialogue Systems
A Data-driven Methodology for Dialogue Management and Natural Language Generation
AvVerena Rieser,Oliver Lemon
Häftad, Engelska, 2014
1 118 kr
Skickas inom 10-15 vardagar
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.

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Oliver Lemon – författare

Data-Driven Methods for Adaptive Spoken Dialogue Systems

Data-Driven Methods for Adaptive Spoken Dialogue Systems

Data-Driven Methods for Adaptive Spoken Dialogue Systems

Reinforcement Learning for Adaptive Dialogue Systems

Reinforcement Learning for Adaptive Dialogue Systems

Reinforcement Learning for Adaptive Dialogue Systems

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