Dario Mana


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Annotating Errors and Emotions in Human-Chatbot Interactions in Italian
Manuela Sanguinetti | Alessandro Mazzei | Viviana Patti | Marco Scalerandi | Dario Mana | Rossana Simeoni
Proceedings of the 14th Linguistic Annotation Workshop

This paper describes a novel annotation scheme specifically designed for a customer-service context where written interactions take place between a given user and the chatbot of an Italian telecommunication company. More specifically, the scheme aims to detect and highlight two aspects: the presence of errors in the conversation on both sides (i.e. customer and chatbot) and the “emotional load” of the conversation. This can be inferred from the presence of emotions of some kind (especially negative ones) in the customer messages, and from the possible empathic responses provided by the agent. The dataset annotated according to this scheme is currently used to develop the prototype of a rule-based Natural Language Generation system aimed at improving the chatbot responses and the customer experience overall.

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Content Selection for Explanation Requests in Customer-Care Domain
Luca Anselma | Mirko Di Lascio | Dario Mana | Alessandro Mazzei | Manuela Sanguinetti
2nd Workshop on Interactive Natural Language Technology for Explainable Artificial Intelligence

This paper describes a content selection module for the generation of explanations in a dialogue system designed for customer care domain. First we describe the construction of a corpus of a dialogues containing explanation requests from customers to a virtual agent of a telco, and second we study and formalize the importance of a specific information content for the generated message. In particular, we adapt the notions of importance and relevance in the case of schematic knowledge bases.