In the project, an approach was developed and implemented to classify chat messages into dialogue acts, focusing on questions and directives (“to-dos”). Our multi-lingual system uses word lexica, a specialized tokenizer and rule-based shallow syntactic analysis to compute relevant features, and then trains statistical models (support vector machines, random forests, etc.) for dialogue act prediction. The classification scores we achieve are very satisfactory on question detection and promising on to-do detection, on English and German data collections.
The goal of this project is to develop technologies for the automatic segmentation and interpretation of audio files and audio streams deriving from different media worlds: music repositories, (Web and terrestrial) radio streams, TV broadcasts, etc. A specific focus is on streams in which music plays an important role.
Interpersonal communication and the coordination and synchronization of actions are fundamental human capacities. People use these functions routinely in activities such as shaking hands, driving a car, playing sports, or playing music as part of an ensemble. To coordinate your actions with someone else’s, you must be able to predict how the other person is going to behave. Music ensemble performance provides a particularly interesting context for studying prediction and coordination because the synchronization between actions must be so precise. Since music is dynamic, or time-varying, ensemble musicians must make predictions about their co-performers’ behaviour as they play, relying primarily on nonverbal cues provided by their co-performers’ body movements, breathing, and sound. This research project investigates the mechanisms underlying musical synchronization in small ensembles, using a combination of perceptual/performance experiments and computational modelling techniques.
Lrn2Cre8 aims to understand the relationship between learning and creativity by means of practical engineering, theoretical study, and cognitive comparison. We begin from the position that creativity is a function of memory, that generates new structures based on memorised ones, by processes which are essentially statistical.
Modern digital multimedia and internet technology have radically changed the ways people find entertainment and discover new interests online, seemingly without any physical or social barriers. Such new access paradigms are in sharp contrast with the traditional means of entertainment. An illustrative example of this is live music concert performances that are largely being attended by dedicated audiences only. The PHENICX project aims at bridging the gap between the online and offline entertainment worlds. It will make use of the state-of-the-art digital multimedia and internet technology to make the traditional concert experiences rich and universally accessible: concerts will become multimodal, multi-perspective and multilayer digital artefacts that can be easily explored, customized, personalized, (re)enjoyed and shared among the users.
The central aim of the study is the realistic presentation of the potential of AAL Robotics, based on the analysis of parameters drawn from user needs, technical readiness, and existing business models. Instead of compiling yet another collection of individual solutions and projects, the PotenziAAL Study will aggregate existing knowledge gained from analysis of secondary sources with knowledge generated from primary sources such as expert interviews, a workshop and user focus groups in order to achieve a comprehensive picture of the state of the art in AAL Robotics and its future potential. The study will develop categories and criteria in order to foster exact characterization, comparability and quality assurance in AAL Robotics.
Generelles Ziel des Projekts „Automated Coding and Categorizing of Innovation Areas“ (ACCIA) war es, ein intelligentes automatisiertes System zu schaffen, das Belegstellen für problembezogene, innovationsrelevante Äußerungen, welche aus unterschiedlichen Online-Quellen extrahiert wurden, identifizieren, analysieren und kategorisieren kann. Durch die Einbindung von Verfahren aus den Bereichen Textverarbeitung, Document Clustering und Document Classification konnte ein Prozessmodell erarbeitet werden, dass eine bisher rein manuell durchgeführte Innovationsfeldanalyse in ein automatisiertes Modell überführt, in dem die manuelle, expertinnengetriebene Analyse mit automatischen, computerlinguistisch gestützten Verfahren verschränkt wird.
The aim of the project is the development of a virtual agent that interactively supports older persons in the narration of autobiographic stories, from listener feedback to raw transcription.
Automated, gender-sensitive approaches as a means to support social media analyses in Social Sciences reseach.
The FemSMA project aims at the development of automatic methods to determine the gender of the author of a given user-created social media posting (e.g. Tweets, blog or internet forum entries). The approach is motivated by recent developments in the social sciences, as well as market and opinion research, which increasingly consider social media platforms as a valuable source of data, especially for trend and sentiment analyses. Current instruments for social media analysis are incapable of providing gender-aware information regarding the topics, products or (political) programmes under investigation. This deficit, as well as the associated lack of orientation towards active demand, will be countered effectively in FemSMA.