arXiv:2606.00851v1 Announce Type: cross Abstract: Empathetic spoken dialogue systems must infer a user's emotional state to respond appropriately, yet everyday speech often carries weak, neutral, or ambiguous affective cues. To address this, we introduce Sympatheia, a speech-to-speech dialogue framework conditioned on affect inferred from the user's speech and, when available, explicit affect specifications provided as a continuous valence--arousal (VA) control signal by a multimodal sensing module or user interface. To train our model, we construct Sympatheia-18k, an emotion-conditioned synth
The continuous advancements in AI, especially in natural language processing and multimodal sensing, are enabling more sophisticated and emotionally aware human-computer interactions.
Emotionally adaptive AI systems like Sympatheia could significantly enhance user experience and engagement, making AI companions and interfaces more intuitive and effective in domains like customer service, healthcare, and education.
AI-driven voice assistants are evolving beyond basic task execution to incorporate nuanced emotional understanding and response, moving closer to truly 'empathetic' interaction.
- · AI developers
- · Customer service platforms
- · Healthcare technology
- · EdTech
- · Monotone voice assistants
- · Rule-based dialogue systems
Wider adoption of emotionally intelligent AI in consumer and enterprise applications.
Increased user reliance on AI for emotional support and nuanced communication becomes a new normal.
Ethical and societal questions arise regarding the nature of artificial empathy and its impact on human relationships.
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Read at arXiv cs.CL