论文解读
GigaChat Audio: Time-aware Large Audio Language Model
音频理解 | 7.4/10
模型评估
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- 模型比较 直接 130 篇 · 含子树 130 篇
论文解读
Hearing Like Humans? Sound Symbolism and Perceptual Alignment in Speech Language Models
多模态模型 | 6.1/10
论文解读
LOGOS: A Living Logic for AI Agent Teams That Evolve With Humans
多模态模型 | 6.1/10
论文解读
Omni-Decision: A Progressive Evidence-State Agent System for Omni-Modal QA
音频理解 | 5.9/10
论文解读
PC-Mix: Partial-Component Audio Spoofing Detection under Mixed Speech and Environmental Sound Conditions
音频伪造检测 | 8.9/10
论文解读
Perceived Annoyance in Multi-source Electric Vehicle AVAS Environments
音频质量评估 | 3.5/10
论文解读
Semantic Sampling via Learnable Observation Front Ends
音频理解 | 5.1/10
论文解读
Simple Features and Honest Calibration for Ambivalence and Hesitancy Recognition in Video
模型集成 | 9.0/10
论文解读
TabPFN beyond Tabular Data: Calibration and Accuracy on Multimodal Embeddings
音频分类 | 7.9/10
论文解读
The SonicAGI System for the REAL-TSE Challenge
语音分离 | 6.8/10
论文解读
Verifier-Guided Twelve-Tone Composition: A Generate-Verify-Repair Harness for Symbolic Music Generation
音乐生成 | 6.0/10
论文解读
VoxENES 2026: Benchmarking Generalization of Speech Spoofing Detectors Against LLM-Era TTS and Voice Conversion
语音伪造检测 | 8.1/10
论文解读
What You Train Is What You Get: Gender Bias, Training Composition, and Post-Hoc Mitigation in Audio Deepfake Detection
语音伪造检测 | 6.6/10
论文解读
Clean2FX: Label-conditioned modeling for clean-to-effect guitar audio transformations
音频理解 | 7.3/10
论文解读
Immersive Social Interaction with VR and LLM-Assisted Humanoids
语音交互 | 4.7/10
论文解读
SVF-CR: Synchronized Visual-Facial Cross-Refinement for Multimodal Ambivalence and Hesitancy Recognition
音视频理解 | 6.4/10
论文解读
Tonnetz-Driven Graph Wedgelet for Harmonic Complexity Reduction in Music Scores
音乐理解 | 5.3/10
论文解读
Wan-Dancer: A Hierarchical Framework for Minute-scale Coherent Music-to-Dance Generation
音乐生成 | 5.6/10
论文解读
A Reliability Assessment of LALM Audio Judges for Full-Duplex Voice Agents
语音质量评估 | 7.1/10
论文解读
A Reliability Assessment of LALM Audio Judges for Full-Duplex Voice Agents
语音质量评估 | 8.7/10