This paper describes metaphors and design strategies used to conceive and develop a hand-held, location-aware tourist guide\ud that delivers information related to the surrounding space mainly by reacting to the physical movements of the visitors. The guide is\ud designed to minimise the boundary between the physical space and the related information through a number of situated and contextual aware interaction mechanisms. These mechanisms are conceived to support the activity both at individual and social level
If understanding sentiments is already a difficult task in human-human communication, this becomes extremely challenging when a human-computer interaction happens, as for instance in chatbot conversations. In this work, a machine learning neural network-based Speech Emotion Recognition system is presented to perform emotion detection in a chatbot virtual assistant whose task was to perform contact tracing during the COVID-19 pandemic. The system was tested on a novel dataset of audio samples, provided by the company Blu Pantheon, which developed virtual agents capable of autonomously performing contacts tracing for individuals positive to COVID-19. The dataset provided was unlabelled for the emotions associated to the conversations. Therefore, the work was structured using a sort of transfer learning strategy. First, the model is trained using the labelled and publicly available Italian-language dataset EMOVO Corpus. The accuracy achieved in testing phase reached 92%. To the best of their knowledge, thiswork represents the first example in the context of chatbot speech emotion recognition for contact tracing, shedding lights towards the importance of the use of such techniques in virtual assistants and chatbot conversational contexts for psychological human status assessment. The code of this work was publicly released at: https://github.com/fp1acm8/SER.
A b s t r a c tCollective or social memories belonging to communities are not just a way for accumulating and preserving but also for sharing and developing knowledge. Indeed, as knowledge is made explicit and elaborated by a community, it enriches the local culture and the current practices, becoming a basis for communication and learning. This paper addresses the concept of 'social memory' in a speci c 'community of practice': teachers and students of primary schools. The work is developed within HIPS 1 (Hyper Interaction within Physical Space), a three-year (1997)(1998)(1999)(2000) research project funded by the European Commission within the I 3 (I-Cube) Programme. HIPS is a hand-held location-aware tourist guide that delivers information related to the surrounding space mainly reacting to the physical movements of visitors (Benelli et al. 1999). The guide is designed to minimize the boundary between the physical space and the related information through a number of situated and contextual-aware interaction mechanisms. In the paper we present a speci c application of HIPS as tool to support the creation of a social memory. First, we illustrate the theoretical framework, the cultural psychology (Vygotsky 1978), which we adopted to design the tool as an external aid for social memory. Afterwards we describe the user study and the design process that resulted in the development of an early prototype. The conclusions are a re ection about the use of new technology to open new learning opportunities for students. K e y w o r d s collective memories, community of practice, learning, knowledge sharing, scenario-based design
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