Sentence structure for dialog act recognition in Czech

This paper deals with automatic dialog acts (DAs) recognition in Czech based on sentence structure. We consider the following DAs: statements, orders, yes/no questions and other questions. In our previous works, we have proposed, implemented and evaluated new approaches to automatic DAs recognition based on sentence structure and prosody. The word sequences were manually transcribed. The main goal of this paper is to evaluate the performances of our approaches when these word sequences are unknown and estimated from a speech recognizer. Our system is tested on a Czech corpus that simulates a task of train tickets reservation. When manual transcription is used, classification accuracy without and with sentence structure models is 91 %, 94 % and 95 %. The recognition accuracy reaches 96 % with prosodic combination. When word sequences are estimated from a speech recognizer, the classification score is 88 % without and 91 % and 92 % with sentence structure models. The combination with prosody gives 93 % of accuracy

Proceedings of the First European Workshop on Latent Semantic Analysis in Technology Enhanced Learning

Latent Semantic Analysis (LSA) has been successfully deployed in various educational applications to enrich learning and teaching with information-technology. The primary goal of the workshop is to bring together experts in the field in order to share knowledge gained within the scattered research about latent semantic analysis in educational applications, in particular from the context of the IST projects Cooper, iCamp,T enCompetence and ProLearn

Proceedings of the First European Workshop on Latent Semantic Analysis in Technology Enhanced Learning

Latent Semantic Analysis (LSA) has been successfully deployed in various educational applications to enrich learning and teaching with information-technology. The primary goal of the workshop is to bring together experts in the field in order to share knowledge gained within the scattered research about latent semantic analysis in educational applications, in particular from the context of the IST projects Cooper, iCamp,T enCompetence and ProLearn

Comunicação humano-robô através de linguagem falada

Doutoramento em Engenharia ElectrotécnicaNos últimos anos, as tecnologias que dão suporte à robótica avançaram expressivamente. É possível encontrar robôs de serviço nos mais variados campos. O próximo passo é o desenvolvimento de robôs inteligentes, com capacidade de comunicação em linguagem falada e de realizar trabalhos úteis em interação/cooperação com humanos. Torna-se necessário, então, encontrar um modo de interagir eficientemente com esses robôs, e com agentes inteligentes de maneira geral, que permita a transmissão de conhecimento em ambos os sentidos. Partiremos da hipótese de que é possível desenvolver um sistema de diálogo baseado em linguagem natural falada que resolva esse problema. Assim, o objetivo principal deste trabalho é a definição, implementação e avaliação de um sistema de diálogo utilizável na interação baseada em linguagem natural falada entre humanos e agentes inteligentes. Ao longo deste texto, mostraremos os principais aspectos da comunicação por linguagem falada, tanto entre os humanos, como também entre humanos e máquinas. Apresentaremos as principais categorias de sistemas de diálogo, com exemplos de alguns sistemas implementados, assim como ferramentas para desenvolvimento e algumas técnicas de avaliação. A seguir, entre outros aspectos, desenvolveremos os seguintes: a evolução levada a efeito na arquitetura computacional do Carl, robô utilizado neste trabalho; o módulo de aquisição e gestão de conhecimento, desenvolvido para dar suporte à interação; e o novo gestor de diálogo, baseado na abordagem de “Estado da Informação”, também concebido e implementado no âmbito desta tese. Por fim, uma avaliação experimental envolvendo a realização de diversas tarefas de interação com vários participantes voluntários demonstrou ser possível interagir com o robô e realizar as tarefas solicitadas. Este trabalho experimental incluiu avaliação parcial de funcionalidades, avaliação global do sistema de diálogo e avaliação de usabilidade.In recent years, robotics-related technologies have reached a remarkable level of maturity. Service robots can be found in various fields. The next step is the development of intelligent robots, capable of communicating in spoken language and doing useful work in interaction / cooperation with humans. It is then necessary to find a way to efficiently interact with these robots, and with intelligent agents in general, enabling the transmission of knowledge in both directions. We will assume that one can develop a spoken language dialogue system to solve this problem. Therefore, the main goal of this work is the design, implementation and evaluation of a dialogue system that can be used on spoken language interaction between humans and intelligent agents. Throughout this document, we present and discuss the main aspects related to spoken language communication, among humans as well as between humans and machines. We present the main dialogue system categories, with examples of some implemented systems, development tools and a few evaluation techniques. Then, we describe the developed dialog system and its integration in a real robot, including the following aspects: the evolution in the computational architecture of Carl, the robot used in this work; the knowledge acquisition and management module, developed to support the interaction; and the new dialogue manager, based on the “Information State” approach, also designed and implemented within this thesis work. Finally, an experimental evaluation involving the completion of several interaction tasks involving several volunteers proved to be possible to interact with the robot and perform the requested tasks. The evaluation includes a partial evaluation of features, an overall evaluation of the dialogue system and a usability evaluation

Entwicklung eines generischen Vorgehensmodells für Text Mining

Vor dem Hintergrund des steigenden Interesses von computergestützter Textanalyse in Forschung und Praxis entwickelt dieser Beitrag auf Basis aktueller Literatur ein generisches Vorgehensmodell für Text-Mining-Prozesse. Das Ziel des Beitrags ist, die dabei anfallenden, umfangreichen Aktivitäten zu strukturieren und dadurch die Komplexität von Text-Mining-Vorhaben zu reduzieren. Das Forschungsziel stützt sich auf die Tatsache, dass im Rahmen einer im Vorfeld durchgeführten, systematischen Literatur-Review keine detaillierten, anwendungsneutralen Vorgehensmodelle für Text Mining identifiziert werden konnten. Aufbauend auf den Erkenntnissen der Literatur-Review enthält das resultierende Modell daher sowohl induktiv begründete Komponenten aus spezifischen Ansätzen als auch aus literaturbasierten Anforderungen deduktiv abgeleitete Bestandteile. Die Evaluation des Artefakts belegt die Nützlichkeit des Vorgehensmodells im Vergleich mit dem bisherigen Forschungsstand.:1 Einführung 1.1 Motivation 1.2 Forschungsziel und Methodik 1.2.1 Systematische Literatur-Review 1.2.2 Design-Science-Research-Ansatz 1.3 Aufbau des Beitrags 2 Stand der Forschung 2.1 Begriffsverständnis 2.2 Merkmale von Vorgehensmodellen für Text Mining 2.3 Aktivitäten im Text-Mining-Prozess 2.4 Zusammenfassung 3 Anforderungen an ein generisches Vorgehensmodell 3.1 Strukturelle Anforderungen 3.2 Funktionelle Anforderungen 3.3 Zusammenfassung 4 Entwicklung des Modells 4.1 Aufgabendefinition 4.2 Dokumentenselektion und -untersuchung 4.3 Dokumentenaufbereitung 4.3.1 Linguistische Aufbereitung 4.3.2 Technische Aufbereitung 4.4 Text-Mining-Verfahren 4.5 Ergebnisevaluation 4.6 Anwendung 4.7 Zusammenfassung 4.7.1 Gesamtmodell 4.7.2 Feedbackschleifen 5 Evaluation 5.1 Evaluationsdesign 5.2 Messung und Auswertung 6 Fazit und Ausblick Literaturverzeichnis Anhang A1 Anwendungsneutrale Vorgehensmodelle A2 Auswirkungen von Grund- und Stammformenreduktion auf die Interpretierbarkeit von Texten A3 Gesamtmodel