Beyond Text: LLM-Based Dimensional Emotion Evaluation in Multimodal Dialogue

arXiv:2609.39072 · cs.CL, cs.AI, cs.LG, cs.MM · Submitted 2026-09-30 · Read on arXiv

cs.CL, cs.AI, cs.LG, cs.MM

Submitted: 2026-09-30

Updated: 2026-09-30

Terminology

• Emotion Recognition — 19× in this paper
• Fine-Tuning — 16× in this paper · explained in 5 episodes
• LoRA Fine-Tuning — 12× in this paper · explained in 3 episodes
• F1 Score — 11× in this paper · explained in 3 episodes
• Prompt Engineering — 8× in this paper · explained in 4 episodes
• Annotator Agreement — 6× in this paper · explained in 1 episode
• Ablation — 5× in this paper · explained in 1 episode
• Adaptation — 5× in this paper · explained in 1 episode
• Actor — 4× in this paper · explained in 3 episodes
• Large Language Models — 4× in this paper
• Ablation Studies — 3× in this paper · explained in 1 episode
• Benchmark — 3× in this paper · explained in 2 episodes
• Feature Extraction — 3× in this paper · explained in 2 episodes
• Frustration — 3× in this paper · explained in 2 episodes
• Ablation study — 2× in this paper · explained in 1 episode
• Domain Adaptation — 2× in this paper · explained in 5 episodes
• Multimodal Dataset — 2× in this paper · explained in 2 episodes
• Parameter-Efficient Fine-Tuning — 2× in this paper · explained in 2 episodes
• alpha — 2× in this paper · explained in 1 episode
• Accuracy — 1× in this paper · explained in 1 episode
• AdamW Optimizer — 1× in this paper · explained in 1 episode
• Adaptive Expert Routing — 1× in this paper · explained in 1 episode
• Affective Computing — 1× in this paper · explained in 1 episode
• Affective Signal — 1× in this paper · explained in 1 episode
• Concordance Correlation Coefficient — 1× in this paper
• Contextual Understanding — 1× in this paper · explained in 2 episodes
• Deep Learning — 1× in this paper
• Embeddings — 1× in this paper · explained in 2 episodes
• Foundation Model — 1× in this paper · explained in 3 episodes
• Foundation Models — 1× in this paper · explained in 7 episodes
• Generalization — 1× in this paper · explained in 13 episodes
• Large Language Models (LLMs) — 1× in this paper · explained in 6 episodes
• Multimodal approach — 1× in this paper · explained in 2 episodes
• Representation Learning — 1× in this paper · explained in 2 episodes
• Self-Supervised Learning — 1× in this paper · explained in 7 episodes

Sources

• SpeechT5: Unified-Modal Encoder-Decoder Pre-Training for Spoken Language Processing
• Two-stage dimensional emotion recognition by fusing predictions of acoustic and text networks using SVM
• wav2vec 2.0: A Framework for Self-Supervised Learning of Speech Representations
• EmotionLines: An Emotion Corpus of Multi-Party Conversations
• GoEmotions: A Dataset of Fine-Grained Emotions
• CLAP: Learning Audio Concepts From Natural Language Supervision
• LoRA: Low-Rank Adaptation of Large Language Models
• A Multi-Task, Multi-Modal Approach for Predicting Categorical and Dimensional Emotions
• Aff-Wild2: Extending the Aff-Wild Database for Affect Recognition
• DeepDialogue: A Multi-Turn Emotionally-Rich Spoken Dialogue Dataset
• DailyDialog: A Manually Labelled Multi-turn Dialogue Dataset
• DialogueRNN: An Attentive RNN for Emotion Detection in Conversations
• EXPRESSO: A Benchmark and Analysis of Discrete Expressive Speech Resynthesis
• MELD: A Multimodal Multi-Party Dataset for Emotion Recognition in Conversations
• Towards Empathetic Open-domain Conversation Models: a New Benchmark and Dataset
• Representation learning through cross-modal conditional teacher-student training for speech emotion recognition
• EmotionTalk: An Interactive Chinese Multimodal Emotion Dataset With Rich Annotations
• Towards Multimodal Empathetic Response Generation: A Rich Text-Speech-Vision Avatar-based Benchmark
• Emotional Voice Conversion: Theory, Databases and ESD

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