FiLMを活用した音声対話における感情的対話破綻検出

抄録

When the same linguistic content carries different acoustic nuances, particularly in terms of expressed emotions, the corresponding dialogue system response must align with the given nuance. However, existing SLMs such as Qwen2-Audio are not necessarily robust against such differences. In this work, we define a task that detects the consistency or inconsistency between the emotional label of an utterance and the system's response, and build a model to perform this prediction. We hypothesize that emotion labels are a control signal that modulates text interpretation, and we construct a prediction model based on Feature-wise Linear Modulation (FiLM).