This research introduces C²SER, a novel approach that improves speech emotion recognition in audio language models by reducing hallucinations through contextual perception and chain-of-thought reasoning.

• Combines contextual awareness with structured reasoning to enhance emotion recognition accuracy
• Addresses critical hallucination problems in current audio language models
• Provides a more stable framework for emotion detection in diverse speech signals
• Enables more reliable analysis for security applications including emotional distress detection

For security professionals, this advancement enables more reliable threat assessment, surveillance monitoring, and emotional distress detection in audio—critical for emergency response and public safety systems.

Original Paper: Steering Language Model to Stable Speech Emotion Recognition via Contextual Perception and Chain of Thought