5 accepted papers
User satisfaction is closely related to enterprises, as it not only directly reflects users' subjective evaluation of service quality or products, but also affects customer loyalty and long-term business revenue. Monitoring and understanding user emotions during interactions helps predict and improv…
Empathy detection (ED) aims to understand the user’s empathy direction, while empathy intent classification (EIC) focuses on identifying the empathy intent behind the user’s utterance. Both tasks have garnered significant attention. Recent studies have shown that jointly training these tasks can imp…
Speaker verification performance significantly degrades when there exists a language mismatch between training and evaluation. Domain Adversarial Training (DAT) has shown to be effective in mitigating this gap by incorporating adversarial training with domain information (language id). Inspired by r…
Empathy detection (ED) and empathy intent classification (EIC) aim to identify the empathy direction expressed in user utterances and the underlying empathy intent behind them. Previous studies show that facilitating information transfer between tasks can enhance model performance. However, the inte…
Empathy plays an important role in the human dialogue. Detecting the empathetic direction expressed by the user is necessary for empathetic dialogue systems because it is highly relevant to understanding the user's needs. Several studies have shown that empathy intent information improves the abilit…