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20242026
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cs.CL2026

Emotion Across Speech and Faces: Shared Affective Mechanisms in Multimodal Foundation Models

Xiutian Zhao, Luqi Sun, Björn Schuller +1

Modern multimodal foundation models (MFMs) have made rapid progress on tasks requiring integrated perception across speech, vision, and language, including emotion recognition. How…

cs.CL2026

Multilingual Emotion Neurons in Large Audio-Language Models

Xiutian Zhao, Philipp Koehn, Björn Schuller +1

Emotion is central to human communication, and its expression varies across languages. Large audio-language models (LALMs) achieve strong performance on multilingual speech tasks,…

cs.CL2026

XAI-Grounded Explanation Generation for Speech Deepfake Detection with Training-Free Multimodal Large Language Models

Yupei Li, Qiyang Sun, Xiaoliang Wu +3

Speech deepfake detection (SDD) systems require trustworthy explanations for reliable decision-making. Existing explanation ways mainly fall into two categories. Traditional explai…

cs.CL2026

Neuron-Level Emotion Control in Speech-Generative Large Audio-Language Models

Xiutian Zhao, Ismail Rasim Ulgen, Philipp Koehn +2

Large audio-language models (LALMs) can produce expressive speech, yet reliable emotion control remains elusive: conversions often miss the target affect and may degrade linguistic…

cs.CL2026

Discovering and Causally Validating Emotion-Sensitive Neurons in Large Audio-Language Models

Xiutian Zhao, Björn Schuller, Björn Schuller +1

Emotion is a central dimension of spoken communication, yet, we still lack a mechanistic account of how modern large audio-language models (LALMs) encode it internally. We present…

cs.CL2025

Multimodal Fine-grained Context Interaction Graph Modeling for Conversational Speech Synthesis

Zhenqi Jia, Rui Liu, Berrak Sisman +1

Conversational Speech Synthesis (CSS) aims to generate speech with natural prosody by understanding the multimodal dialogue history (MDH). The latest work predicts the accurate pro…