Rim Helaoui


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Towards Low-Resource Real-Time Assessment of Empathy in Counselling
Zixiu Wu | Rim Helaoui | Diego Reforgiato Recupero | Daniele Riboni
Proceedings of the Seventh Workshop on Computational Linguistics and Clinical Psychology: Improving Access

Gauging therapist empathy in counselling is an important component of understanding counselling quality. While session-level empathy assessment based on machine learning has been investigated extensively, it relies on relatively large amounts of well-annotated dialogue data, and real-time evaluation has been overlooked in the past. In this paper, we focus on the task of low-resource utterance-level binary empathy assessment. We train deep learning models on heuristically constructed empathy vs. non-empathy contrast in general conversations, and apply the models directly to therapeutic dialogues, assuming correlation between empathy manifested in those two domains. We show that such training yields poor performance in general, probe its causes, and examine the actual effect of learning from empathy contrast in general conversation.


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Interactive health insight miner: an adaptive, semantic-based approach
Isabel Funke | Rim Helaoui | Aki Härmä
Proceedings of the 11th International Conference on Natural Language Generation

E-health applications aim to support the user in adopting healthy habits. An important feature is to provide insights into the user’s lifestyle. To actively engage the user in the insight mining process, we propose an ontology-based framework with a Controlled Natural Language interface, which enables the user to ask for specific insights and to customize personal information.