论文解读
Multi-View Hierarchical Hypergraph Neural Network for Automatic Stuttering Detection
语音生物标志物 | 7.5/10
语音情感识别
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Multimodal Self-Attention Network with Temporal Alignment for Audio-Visual Emotion Recognition
语音情感识别 | 8.0/10
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Multimodal Variational Graph Network for Multimodal Sentiment Analysis
语音情感识别 | 7.5/10
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Plug-and-Play Emotion Graphs for Compositional Prompting in Zero-Shot Speech Emotion Recognition
语音情感识别 | 7.0/10
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Prompt-Guided Mixture-of-Experts for Robust Multimodal Sentiment Analysis with Missing Modalities
语音情感识别 | 8.5/10
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Rationale-Guided Learning for Multimodal Emotion Recognition
语音情感识别 | 7.0/10
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Reasoning Driven Captions to Assist Noise Robust Speech Emotion Recognition
语音情感识别 | 7.0/10
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Recovering Performance in Speech Emotion Recognition from Discrete Tokens Via Multi-Layer Fusion and Paralinguistic Feature Integration
语音情感识别 | 6.5/10
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Scaling Ambiguity: Augmenting Human Annotation in Speech Emotion Recognition with Audio-Language Models
语音情感识别 | 6.5/10
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SmoothCLAP: Soft-Target Enhanced Contrastive Language-Audio Pretraining for Affective Computing
语音情感识别 | 6.5/10
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Speaker Anonymisation for Speech-Based Suicide Risk Detection
语音匿名化 | 7.5/10
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Speech Emotion Recognition based on Hierarchical Transformer with Shifted Windows
语音情感识别 | 8.0/10
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Staged Diffusion with Hybrid Mixture-of-Experts (MOE) for Multimodal Sentiment Analysis
语音情感识别 | 8.0/10
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Stress Prediction from Temporal Emotion Trajectories in Clinical Patient-Physician Conversations
语音情感识别 | 7.0/10
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StyleBench: Evaluating Speech Language Models on Conversational Speaking Style Control
基准测试 | 8.5/10
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SURE: Synergistic Uncertainty-Aware Reasoning for Multimodal Emotion Recognition in Conversations
语音情感识别 | 7.5/10
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Synthetic yet Striking? Assessing Vocal Charisma in TTS via Perceptual and Algorithmic Measures
语音合成 | 7.5/10
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Temporal Graph Modeling for Speech Emotion Recognition Using LSTM-Aggregated Multigraph Networks
语音情感识别 | 7.5/10
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Test Time Adaptation for Speech Emotion Recognition
语音情感识别 | 7.0/10
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Tpeformer: Temporal Patch Embedding Transformer
语音情感识别 | 7.5/10