论文解读
RRPO: Robust Reward Policy Optimization for LLM-Based Emotional TTS
语音合成 | 7.5/10
鲁棒性
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- 对抗鲁棒性 直接 58 篇 · 含子树 58 篇
论文解读
Sampling-Rate-Agnostic Speech Super-Resolution Based on Gaussian Process Dynamical Systems with Deep Kernel Learning
语音增强 | 6.5/10
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Snore Sound Classification Based on Physiological Features and Adaptive Loss Function
音频分类 | 6.5/10
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Spectral or Spatial? Leveraging Both for Speaker Extraction in Challenging Data Conditions
语音分离 | 7.0/10
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Spectrogram Event Based Feature Representation for Generalizable Automatic Music Transcription
音乐信息检索 | 7.5/10
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Spiking Attention Network: A Hybrid Neuromorphic Approach to Underwater Acoustic Localization and Zero-Shot Adaptation
声源定位 | 7.0/10
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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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StreamMark: A Deep Learning-Based Semi-Fragile Audio Watermarking for Proactive Deepfake Detection
音频深度伪造检测 | 8.0/10
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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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Target-Speaker LLM-ASR with Speaker-Aware Speech Encoder
语音识别 | 8.8/10
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Toward Robust And Efficient Beat Tracking Via Beat-Aware Attention
音乐理解 | 8.5/10
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Towards Blind Data Cleaning: A Case Study in Music Source Separation
音乐信息检索 | 7.0/10
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Towards Lightweight Adaptation of Speech Enhancement Models in Real-World Environments
语音增强 | 8.5/10
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Towards Robust Dysarthric Speech Recognition: LLM-Agent Post-ASR Correction Beyond WER
语音识别 | 9.0/10
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Training Flow Matching Models with Reliable Labels via Self-Purification
语音合成 | 7.5/10
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Transferable Audio Lottery Tickets: Gradient Accumulation for Extreme Sparsity
音频分类 | 7.0/10
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Two-Stage Language Model Framework for Acoustic Echo Cancellation
语音增强 | 7.5/10
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UMV: A Mixture-Of-Experts Vision Transformer with Multi-Spectrogram Fusion for Underwater Ship Noise Classification
音频分类 | 7.5/10
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UNet-Based Fusion and Exponential Moving Average Adaptation for Noise-Robust Speaker Recognition
说话人验证 | 7.5/10
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Unseen but Not Unknown: Using Dataset Concealment to Robustly Evaluate Speech Quality Estimation Models
语音质量评估 | 8.3/10