188 research outputs found
Social talk capabilities for dialogue systems
Small talk capabilities are an important but very challenging extension to dialogue systems. Small talk (or social talk) refers to a kind of conversation, which does not focus on the exchange of information, but on the negotiation of social roles and situations. The goal of this thesis is to provide knowledge, processes and structures that can be used by dialogue systems to satisfactorily participate in social conversations. For this purpose the thesis presents research in the areas of natural-language understanding, dialogue management and error handling. Nine new models of social talk based on a data analysis of small talk conversations are described. The functionally-motivated and content-abstract models can be used for small talk conversations on various topics. The basic elements of the models consist of dialogue acts for social talk newly developed on basis of social science theory. The thesis also presents some conversation strategies for the treatment of so-called out-of-domain (OoD) utterances that can be used to avoid errors in the input understanding of dialogue systems. Additionally, the thesis describes a new extension to dialogue management that flexibly manages interwoven dialogue threads. The small talk models as well as the strategies for handling OoD utterances are encoded as computational dialogue threads
Social talk capabilities for dialogue systems
Small talk capabilities are an important but very challenging extension to dialogue systems. Small talk (or “social talk”) refers to a kind of conversation, which does not focus on the exchange of information, but on the negotiation of social roles and situations. The goal of this thesis is to provide knowledge, processes and structures that can be used by dialogue systems to satisfactorily participate in social conversations. For this purpose the thesis presents research in the areas of natural-language understanding, dialogue management and error handling. Nine new models of social talk based on a data analysis of small talk conversations are described. The functionally-motivated and content-abstract models can be used for small talk conversations on various topics. The basic elements of the models consist of dialogue acts for social talk newly developed on basis of social science theory. The thesis also presents some conversation strategies for the treatment of so-called “out-of-domain” (OoD) utterances that can be used to avoid errors in the input understanding of dialogue systems. Additionally, the thesis describes a new extension to dialogue management that flexibly manages interwoven dialogue threads. The small talk models as well as the strategies for handling OoD utterances are encoded as computational dialogue threads
Human-Robot Interaction architecture for interactive and lively social robots
Mención Internacional en el título de doctorLa sociedad está experimentando un proceso de envejecimiento que puede provocar un desequilibrio
entre la población en edad de trabajar y aquella fuera del mercado de trabajo. Una de las soluciones
a este problema que se están considerando hoy en día es la introducción de robots en multiples
sectores, incluyendo el de servicios. Sin embargo, para que esto sea una solución viable, estos robots
necesitan ser capaces de interactuar con personas de manera satisfactoria, entre otras habilidades. En
el contexto de la aplicación de robots sociales al cuidado de mayores, esta tesis busca proporcionar
a un robot social las habilidades necesarias para crear interacciones entre humanos y robots que
sean naturales. En concreto, esta tesis se centra en tres problemas que deben ser solucionados: (i) el
modelado de interacciones entre humanos y robots; (ii) equipar a un robot social con las capacidades
expresivas necesarias para una comunicación satisfactoria; y (iii) darle al robot una apariencia vivaz.
La solución al problema de modelado de diálogos presentada en esta tesis propone diseñar estos
diálogos como una secuencia de elementos atómicos llamados Actos Comunicativos (CAs, por sus
siglas en inglés). Se pueden parametrizar en tiempo de ejecución para completar diferentes objetivos
comunicativos, y están equipados con mecanismos para manejar algunas de las imprecisiones que
pueden aparecer durante interacciones. Estos CAs han sido identificados a partir de la combinación
de dos dimensiones: iniciativa (si la tiene el robot o el usuario) e intención (si se pretende obtener o
proporcionar información). Estos CAs pueden ser combinados siguiendo una estructura jerárquica
para crear estructuras mas complejas que sean reutilizables. Esto simplifica el proceso para crear
nuevas interacciones, permitiendo a los desarrolladores centrarse exclusivamente en diseñar el flujo
del diálogo, sin tener que preocuparse de reimplementar otras funcionalidades que tienen que estar
presentes en todas las interacciones (como el manejo de errores, por ejemplo).
La expresividad del robot está basada en el uso de una librería de gestos, o expresiones,
multimodales predefinidos, modelados como estructuras similares a máquinas de estados. El
módulo que controla la expresividad recibe peticiones para realizar dichas expresiones, planifica
su ejecución para evitar cualquier conflicto que pueda aparecer, las carga, y comprueba que su
ejecución se complete sin problemas. El sistema es capaz también de generar estas expresiones en
tiempo de ejecución a partir de una lista de acciones unimodales (como decir una frase, o mover una
articulación). Una de las características más importantes de la arquitectura de expresividad propuesta
es la integración de una serie de métodos de modulación que pueden ser usados para modificar los
gestos del robot en tiempo de ejecución. Esto permite al robot adaptar estas expresiones en base
a circunstancias particulares (aumentando al mismo tiempo la variabilidad de la expresividad del robot), y usar un número limitado de gestos para mostrar diferentes estados internos (como el estado
emocional).
Teniendo en cuenta que ser reconocido como un ser vivo es un requisito para poder participar en
interacciones sociales, que un robot social muestre una apariencia de vivacidad es un factor clave
en interacciones entre humanos y robots. Para ello, esta tesis propone dos soluciones. El primer
método genera acciones a través de las diferentes interfaces del robot a intervalos. La frecuencia e
intensidad de estas acciones están definidas en base a una señal que representa el pulso del robot.
Dicha señal puede adaptarse al contexto de la interacción o al estado interno del robot. El segundo
método enriquece las interacciones verbales entre el robot y el usuario prediciendo los gestos no
verbales más apropiados en base al contenido del diálogo y a la intención comunicativa del robot.
Un modelo basado en aprendizaje automático recibe la transcripción del mensaje verbal del robot,
predice los gestos que deberían acompañarlo, y los sincroniza para que cada gesto empiece en el
momento preciso. Este modelo se ha desarrollado usando una combinación de un encoder diseñado
con una red neuronal Long-Short Term Memory, y un Conditional Random Field para predecir la
secuencia de gestos que deben acompañar a la frase del robot.
Todos los elementos presentados conforman el núcleo de una arquitectura de interacción
humano-robot modular que ha sido integrada en múltiples plataformas, y probada bajo diferentes
condiciones. El objetivo central de esta tesis es contribuir al área de interacción humano-robot
con una nueva solución que es modular e independiente de la plataforma robótica, y que se centra
en proporcionar a los desarrolladores las herramientas necesarias para desarrollar aplicaciones que
requieran interacciones con personas.Society is experiencing a series of demographic changes that can result in an unbalance between
the active working and non-working age populations. One of the solutions considered to mitigate
this problem is the inclusion of robots in multiple sectors, including the service sector. But for
this to be a viable solution, among other features, robots need to be able to interact with humans
successfully. This thesis seeks to endow a social robot with the abilities required for a natural
human-robot interactions. The main objective is to contribute to the body of knowledge on the area
of Human-Robot Interaction with a new, platform-independent, modular approach that focuses on
giving roboticists the tools required to develop applications that involve interactions with humans. In
particular, this thesis focuses on three problems that need to be addressed: (i) modelling interactions
between a robot and an user; (ii) endow the robot with the expressive capabilities required for a
successful communication; and (iii) endow the robot with a lively appearance.
The approach to dialogue modelling presented in this thesis proposes to model dialogues as a
sequence of atomic interaction units, called Communicative Acts, or CAs. They can be parametrized
in runtime to achieve different communicative goals, and are endowed with mechanisms oriented to
solve some of the uncertainties related to interaction. Two dimensions have been used to identify the
required CAs: initiative (the robot or the user), and intention (either retrieve information or to convey
it). These basic CAs can be combined in a hierarchical manner to create more re-usable complex
structures. This approach simplifies the creation of new interactions, by allowing developers to focus
exclusively on designing the flow of the dialogue, without having to re-implement functionalities
that are common to all dialogues (like error handling, for example).
The expressiveness of the robot is based on the use of a library of predefined multimodal gestures,
or expressions, modelled as state machines. The module managing the expressiveness receives requests
for performing gestures, schedules their execution in order to avoid any possible conflict that might
arise, loads them, and ensures that their execution goes without problems. The proposed approach
is also able to generate expressions in runtime based on a list of unimodal actions (an utterance,
the motion of a limb, etc...). One of the key features of the proposed expressiveness management
approach is the integration of a series of modulation techniques that can be used to modify the
robot’s expressions in runtime. This would allow the robot to adapt them to the particularities of a
given situation (which would also increase the variability of the robot expressiveness), and to display
different internal states with the same expressions. Considering that being recognized as a living being is a requirement for engaging in social
encounters, the perception of a social robot as a living entity is a key requirement to foster
human-robot interactions. In this dissertation, two approaches have been proposed. The first
method generates actions for the different interfaces of the robot at certain intervals. The frequency
and intensity of these actions are defined by a signal that represents the pulse of the robot, which can
be adapted to the context of the interaction or the internal state of the robot. The second method
enhances the robot’s utterance by predicting the appropriate non-verbal expressions that should
accompany them, according to the content of the robot’s message, as well as its communicative
intention. A deep learning model receives the transcription of the robot’s utterances, predicts
which expressions should accompany it, and synchronizes them, so each gesture selected starts at
the appropriate time. The model has been developed using a combination of a Long-Short Term
Memory network-based encoder and a Conditional Random Field for generating a sequence of
gestures that are combined with the robot’s utterance.
All the elements presented above conform the core of a modular Human-Robot Interaction
architecture that has been integrated in multiple platforms, and tested under different conditions.Programa de Doctorado en Ingeniería Eléctrica, Electrónica y Automática por la Universidad Carlos III de MadridPresidente: Fernando Torres Medina.- Secretario: Concepción Alicia Monje Micharet.- Vocal: Amirabdollahian Farshi
Natural Language Processing in-and-for Design Research
We review the scholarly contributions that utilise Natural Language
Processing (NLP) methods to support the design process. Using a heuristic
approach, we collected 223 articles published in 32 journals and within the
period 1991-present. We present state-of-the-art NLP in-and-for design research
by reviewing these articles according to the type of natural language text
sources: internal reports, design concepts, discourse transcripts, technical
publications, consumer opinions, and others. Upon summarizing and identifying
the gaps in these contributions, we utilise an existing design innovation
framework to identify the applications that are currently being supported by
NLP. We then propose a few methodological and theoretical directions for future
NLP in-and-for design research
Situated grounding and understanding of structured low-resource expert data
Conversational agents are becoming more widespread, varying from social to goaloriented to multi-modal dialogue systems. However, for systems with both visual
and spatial requirements, such as situated robot planning, developing accurate goaloriented dialogue systems can be extremely challenging, especially in dynamic environments, such as underwater or first responders. Furthermore, training data-driven
algorithms in these domains is challenging due to the esoteric nature of the interaction, which requires expert input. We derive solutions for creating a collaborative
multi-modal conversational agent for setting high-level mission goals. We experiment with state-of-the-art deep learning models and techniques and create a new
data-driven method (MAPERT) that is capable of processing language instructions
by grounding the necessary elements using various types of input data (vision from
a map, text and other metadata). The results show that, depending on the task,
the accuracy of data-driven systems can vary dramatically depending on the type
of metadata and the attention mechanisms that are used. Finally, we are dealing
with low-resource expert data and this inspired the use of the Continual Learning
and Human In The Loop methodology with encouraging results
Fourth Conference on Artificial Intelligence for Space Applications
Proceedings of a conference held in Huntsville, Alabama, on November 15-16, 1988. The Fourth Conference on Artificial Intelligence for Space Applications brings together diverse technical and scientific work in order to help those who employ AI methods in space applications to identify common goals and to address issues of general interest in the AI community. Topics include the following: space applications of expert systems in fault diagnostics, in telemetry monitoring and data collection, in design and systems integration; and in planning and scheduling; knowledge representation, capture, verification, and management; robotics and vision; adaptive learning; and automatic programming
Proceedings of the Seventh Italian Conference on Computational Linguistics CLiC-it 2020
On behalf of the Program Committee, a very warm welcome to the Seventh Italian Conference on Computational Linguistics (CLiC-it 2020). This edition of the conference is held in Bologna and organised by the University of Bologna. The CLiC-it conference series is an initiative of the Italian Association for Computational Linguistics (AILC) which, after six years of activity, has clearly established itself as the premier national forum for research and development in the fields of Computational Linguistics and Natural Language Processing, where leading researchers and practitioners from academia and industry meet to share their research results, experiences, and challenges
Unpacking Creativity for Language Teaching
Before unlocking creativity, we must first unpack what it means. In this book, creativity is unravelled from various perspectives and the relevance for language teaching and learning is explored.
Tin offers a coherent discussion of creativity, adopting an inclusive and integrated but, at the same time, focused approach to creativity. Divided into 12 chapters, the book covers:
• A critical review of the way the term ‘creativity’ is used, defined and written about in various disciplines
• Various models and theories of creativity, the product- and process-oriented views of creativity and their relevance for language teaching
• Three pillars on which creative language pedagogy should be based
• Over 60 practical tasks, applying theoretical arguments and principles of creativity to language teaching and learning.
Based on the author’s own practice and research on creativity over the last two decades, the book provides exciting new ideas for scholars and practitioners interested in creativity and creative language pedagogy. The book serves as an important contribution for students, teachers and scholars in the field of applied linguistics, language teaching and education
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