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

On the Combination of Game-Theoretic Learning and Multi Model Adaptive Filters

This paper casts coordination of a team of robots within the framework of game theoretic learning algorithms. In particular a novel variant of fictitious play is proposed, by considering multi-model adaptive filters as a method to estimate other players’ strategies. The proposed algorithm can be used as a coordination mechanism between players when they should take decisions under uncertainty. Each player chooses an action after taking into account the actions of the other players and also the uncertainty. Uncertainty can occur either in terms of noisy observations or various types of other players. In addition, in contrast to other game-theoretic and heuristic algorithms for distributed optimisation, it is not necessary to find the optimal parameters a priori. Various parameter values can be used initially as inputs to different models. Therefore, the resulting decisions will be aggregate results of all the parameter values. Simulations are used to test the performance of the proposed methodology against other game-theoretic learning algorithms.</p

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

Foundations of Security Analysis and Design III, FOSAD 2004/2005- Tutorial Lectures

he increasing relevance of security to real-life applications, such as electronic commerce and Internet banking, is attested by the fast-growing number of research groups, events, conferences, and summer schools that address the study of foundations for the analysis and the design of security aspects. This book presents thoroughly revised versions of eight tutorial lectures given by leading researchers during two International Schools on Foundations of Security Analysis and Design, FOSAD 2004/2005, held in Bertinoro, Italy, in September 2004 and September 2005. The lectures are devoted to: Justifying a Dolev-Yao Model under Active Attacks, Model-based Security Engineering with UML, Physical Security and Side-Channel Attacks, Static Analysis of Authentication, Formal Methods for Smartcard Security, Privacy-Preserving Database Systems, Intrusion Detection, Security and Trust Requirements Engineering

Using formal logic to represent sign language phonetics in semi-automatic annotation tasks

Cette thèse présente le développement d'un framework formel pour la représentation des Langues de Signes (LS), les langages des communautés Sourdes, dans le cadre de la construction d'un système de reconnaissance automatique. Les LS sont de langues naturelles, qui utilisent des gestes et l'espace autour du signeur pour transmettre de l'information. Cela veut dire que, à différence des langues vocales, les morphèmes en LS ne correspondent pas aux séquences de sons; ils correspondent aux séquences de postures corporelles très spécifiques, séparés par des changements tels que de mouvements. De plus, lors du discours les signeurs utilisent plusieurs parties de leurs corps (articulateurs) simultanément, ce qui est difficile à capturer avec un système de notation écrite. Cette situation difficulté leur représentation dans de taches de Traitement Automatique du Langage Naturel (TALN). Pour ces raisons, le travail présenté dans ce document a comme objectif la construction d'une représentation abstraite de la LS; plus précisément, le but est de pouvoir représenter des collections de vidéo LS (corpus) de manière formelle. En générale, il s'agit de construire une couche de représentation intermédiaire, permettant de faire de la reconnaissance automatique indépendamment des technologies de suivi et des corpus utilisés pour la recherche. Cette couche corresponde à un système de transition d'états (STE), spécialement crée pour représenter la nature parallèle des LS. En plus, elle peut-être annoté avec de formules logiques pour son analyse, à travers de la vérification de modèles. Pour représenter les propriétés à vérifier, une logique multi-modale a été choisi : la Logique Propositionnelle Dynamique (PDL). Cette logique a été originalement crée pour la spécification de programmes. De manière plus précise, PDL permit d'utilise des opérateurs modales comme [a] et , représentant > et >, respectivement. Une variante particulaire a été développée pour les LS : la PDL pour Langue de Signes (PDLSL), qui est interprété sur des STE représentant des corpus. Avec PDLSL, chaque articulateur du corps (comme les mains et la tête) est vu comme un agent indépendant; cela veut dire que chacun a ses propres actions et propositions possibles, et qu'il peux les exécuter pour influencer une posture gestuelle. L'utilisation du framework proposé peut aider à diminuer deux problèmes importantes qui existent dans l'étude linguistique des LS : hétérogénéité des corpus et la manque des systèmes automatiques d'aide à l'annotation. De ce fait, un chercheur peut rendre exploitables des corpus existants en les transformant vers des STE. Finalement, la création de cet outil à permit l'implémentation d'un système d'annotation semi-automatique, basé sur les principes théoriques du formalisme. Globalement, le système reçoit des vidéos LS et les transforme dans un STE valide. Ensuite, un module fait de la vérification formelle sur le STE, en utilisant une base de données de formules crée par un expert en LS. Les formules représentent des propriétés lexicales à chercher dans le STE. Le produit de ce processus, est une annotation qui peut être corrigé par des utilisateurs humains, et qui est utilisable dans des domaines d'études tels que la linguistique.This thesis presents a formal framework for the representation of Signed Languages (SLs), the languages of Deaf communities, in semi-automatic recognition tasks. SLs are complex visio-gestural communication systems; by using corporal gestures, signers achieve the same level of expressivity held by sound-based languages like English or French. However, unlike these, SL morphemes correspond to complex sequences of highly specific body postures, interleaved with postural changes: during signing, signers use several parts of their body simultaneously in order to combinatorially build phonemes. This situation, paired with an extensive use of the three-dimensional space, make them difficult to represent with tools already existent in Natural Language Processing (NLP) of vocal languages. For this reason, the current work presents the development of a formal representation framework, intended to transform SL video repositories (corpus) into an intermediate representation layer, where automatic recognition algorithms can work under better conditions. The main idea is that corpora can be described with a specialized Labeled Transition System (LTS), which can then be annotated with logic formulae for its study. A multi-modal logic was chosen as the basis of the formal language: the Propositional Dynamic Logic (PDL). This logic was originally created to specify and prove properties on computer programs. In particular, PDL uses the modal operators [a] and to denote necessity and possibility, respectively. For SLs, a particular variant based on the original formalism was developed: the PDL for Sign Language (PDLSL). With the PDLSL, body articulators (like the hands or head) are interpreted as independent agents; each articulator has its own set of valid actions and propositions, and executes them without influence from the others. The simultaneous execution of different actions by several articulators yield distinct situations, which can be searched over an LTS with formulae, by using the semantic rules of the logic. Together, the use of PDLSL and the proposed specialized data structures could help curb some of the current problems in SL study; notably the heterogeneity of corpora and the lack of automatic annotation aids. On the same vein, this may not only increase the size of the available datasets, but even extend previous results to new corpora; the framework inserts an intermediate representation layer which can serve to model any corpus, regardless of its technical limitations. With this, annotations is possible by defining with formulae the characteristics to annotate. Afterwards, a formal verification algorithm may be able to find those features in corpora, as long as they are represented as consistent LTSs. Finally, the development of the formal framework led to the creation of a semi-automatic annotator based on the presented theoretical principles. Broadly, the system receives an untreated corpus video, converts it automatically into a valid LTS (by way of some predefined rules), and then verifies human-created PDLSL formulae over the LTS. The final product, is an automatically generated sub-lexical annotation, which can be later corrected by human annotators for their use in other areas such as linguistics

Using formal logic to represent sign language phonetics in semi-automatic annotation tasks

This thesis presents a formal framework for the representation of Signed Languages (SLs), the languages of Deaf communities, in semi-automatic recognition tasks. SLs are complex visio-gestural communication systems; by using corporal gestures, signers achieve the same level of expressivity held by sound-based languages like English or French. However, unlike these, SL morphemes correspond to complex sequences of highly specific body postures, interleaved with postural changes: during signing, signers use several parts of their body simultaneously in order to combinatorially build phonemes. This situation, paired with an extensive use of the three-dimensional space, make them difficult to represent with tools already existent in Natural Language Processing (NLP) of vocal languages. For this reason, the current work presents the development of a formal representation framework, intended to transform SL video repositories (corpus) into an intermediate representation layer, where automatic recognition algorithms can work under better conditions. The main idea is that corpora can be described with a specialized Labeled Transition System (LTS), which can then be annotated with logic formulae for its study. A multi-modal logic was chosen as the basis of the formal language: the Propositional Dynamic Logic (PDL). This logic was originally created to specify and prove properties on computer programs. In particular, PDL uses the modal operators [a] and to denote necessity and possibility, respectively. For SLs, a particular variant based on the original formalism was developed: the PDL for Sign Language (PDLSL). With the PDLSL, body articulators (like the hands or head) are interpreted as independent agents; each articulator has its own set of valid actions and propositions, and executes them without influence from the others. The simultaneous execution of different actions by several articulators yield distinct situations, which can be searched over an LTS with formulae, by using the semantic rules of the logic. Together, the use of PDLSL and the proposed specialized data structures could help curb some of the current problems in SL study; notably the heterogeneity of corpora and the lack of automatic annotation aids. On the same vein, this may not only increase the size of the available datasets, but even extend previous results to new corpora; the framework inserts an intermediate representation layer which can serve to model any corpus, regardless of its technical limitations. With this, annotations is possible by defining with formulae the characteristics to annotate. Afterwards, a formal verification algorithm may be able to find those features in corpora, as long as they are represented as consistent LTSs. Finally, the development of the formal framework led to the creation of a semi-automatic annotator based on the presented theoretical principles. Broadly, the system receives an untreated corpus video, converts it automatically into a valid LTS (by way of some predefined rules), and then verifies human-created PDLSL formulae over the LTS. The final product, is an automatically generated sub-lexical annotation, which can be later corrected by human annotators for their use in other areas such as linguistics.Cette thèse présente le développement d'un framework formel pour la représentation des Langues de Signes (LS), les langages des communautés Sourdes, dans le cadre de la construction d'un système de reconnaissance automatique. Les LS sont de langues naturelles, qui utilisent des gestes et l'espace autour du signeur pour transmettre de l'information. Cela veut dire que, à différence des langues vocales, les morphèmes en LS ne correspondent pas aux séquences de sons; ils correspondent aux séquences de postures corporelles très spécifiques, séparés par des changements tels que de mouvements. De plus, lors du discours les signeurs utilisent plusieurs parties de leurs corps (articulateurs) simultanément, ce qui est difficile à capturer avec un système de notation écrite. Cette situation difficulté leur représentation dans de taches de Traitement Automatique du Langage Naturel (TALN). Pour ces raisons, le travail présenté dans ce document a comme objectif la construction d'une représentation abstraite de la LS; plus précisément, le but est de pouvoir représenter des collections de vidéo LS (corpus) de manière formelle. En générale, il s'agit de construire une couche de représentation intermédiaire, permettant de faire de la reconnaissance automatique indépendamment des technologies de suivi et des corpus utilisés pour la recherche. Cette couche corresponde à un système de transition d'états (STE), spécialement crée pour représenter la nature parallèle des LS. En plus, elle peut-être annoté avec de formules logiques pour son analyse, à travers de la vérification de modèles. Pour représenter les propriétés à vérifier, une logique multi-modale a été choisi : la Logique Propositionnelle Dynamique (PDL). Cette logique a été originalement crée pour la spécification de programmes. De manière plus précise, PDL permit d'utilise des opérateurs modales comme [a] et , représentant > et >, respectivement. Une variante particulaire a été développée pour les LS : la PDL pour Langue de Signes (PDLSL), qui est interprété sur des STE représentant des corpus. Avec PDLSL, chaque articulateur du corps (comme les mains et la tête) est vu comme un agent indépendant; cela veut dire que chacun a ses propres actions et propositions possibles, et qu'il peux les exécuter pour influencer une posture gestuelle. L'utilisation du framework proposé peut aider à diminuer deux problèmes importantes qui existent dans l'étude linguistique des LS : hétérogénéité des corpus et la manque des systèmes automatiques d'aide à l'annotation. De ce fait, un chercheur peut rendre exploitables des corpus existants en les transformant vers des STE. Finalement, la création de cet outil à permit l'implémentation d'un système d'annotation semi-automatique, basé sur les principes théoriques du formalisme. Globalement, le système reçoit des vidéos LS et les transforme dans un STE valide. Ensuite, un module fait de la vérification formelle sur le STE, en utilisant une base de données de formules crée par un expert en LS. Les formules représentent des propriétés lexicales à chercher dans le STE. Le produit de ce processus, est une annotation qui peut être corrigé par des utilisateurs humains, et qui est utilisable dans des domaines d'études tels que la linguistique