8 citations · 9 across the 4 of their papers we have counts for
4 papers
A Customer Journey in the Land of Oz: Leveraging the Wizard of Oz Technique to Model Emotions in Customer Service Interactions
Sofie Labat, Thomas Demeester, Véronique Hoste
Emotion-aware customer service needs in-domain conversational data, rich annotations, and predictive capabilities, but existing resources for emotion recognition are often out-of-d…
Why Robots Are Bad at Detecting Their Mistakes: Limitations of Miscommunication Detection in Human-Robot Dialogue
Ruben Janssens, Jens De Bock, Sofie Labat +3
Detecting miscommunication in human-robot interaction is a critical function for maintaining user engagement and trust. While humans effortlessly detect communication errors in con…
EmoTwiCS: A Corpus for Modelling Emotion Trajectories in Dutch Customer Service Dialogues on Twitter
Sofie Labat, Thomas Demeester, Véronique Hoste
Due to the rise of user-generated content, social media is increasingly adopted as a channel to deliver customer service. Given the public character of these online platforms, the…
A Million Tweets Are Worth a Few Points: Tuning Transformers for Customer Service Tasks
Amir Hadifar, Sofie Labat, Véronique Hoste +2
In online domain-specific customer service applications, many companies struggle to deploy advanced NLP models successfully, due to the limited availability of and noise in their d…