论文解读
TASTE: Text-Aligned Speech Tokenization and Embedding for Spoken Language Modeling
语音生成 | 7.0/10
少样本
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Better Together: Leveraging Unpaired Multimodal Data for Stronger Unimodal Models
多模态模型 | 7.0/10
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Few-Shot Accent Synthesis for ASR with LLM-Guided Phoneme Editing
语音识别 | 7.5/10
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Hankel and Toeplitz Rank-1 Decomposition of Arbitrary Matrices with Applications to Signal Direction-of-Arrival Estimation
声源定位 | 7.5/10
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A Bayesian Approach to Singing Skill Evaluation Using Semitone Pitch Histogram and MCMC-Based Generated Quantities
音乐理解 | 7.0/10
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Denoising Of Stochastic Ray Tracing Room Impulse Responses
空间音频 | 7.5/10
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EdgeSpot: Efficient and High-Performance Few-Shot Model for Keyword Spotting
语音活动检测 | 7.5/10
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EMG-to-Speech with Fewer Channels
语音合成 | 7.5/10
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Improving Active Learning for Melody Estimation by Disentangling Uncertainties
音乐信息检索 | 7.5/10
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LLM-Based Post-ASR Error Correction for Disordered Speech
语音识别 | 7.5/10
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Low-Resource Speech-Based Early Alzheimers Detection via Cross-Lingual and Few-Shot Transfer Learning
语音生物标志物 | 7.5/10
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Monitoring exposure-length variations in submarine power cables using distributed fiber-optic sensing
音频事件检测 | 6.5/10
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Multimodal Fusion-Based IPCLIP Network for Mixed Reality Surgical Assistance
多模态模型 | 6.5/10
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QFOCUS: Controllable Synthesis for Automated Speech Stress Editing to Deliver Human-Like Emphatic Intent
语音合成 | 7.5/10
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Separate this, and all of these Things Around It: Music Source Separation Via Hyperellipsoidal Queries
音乐分离 | 7.0/10
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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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Synthetic Data Domain Adaptation for ASR via LLM-Based Text and Phonetic Respelling Augmentation
语音识别 | 8.0/10
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Variational Low-Rank Adaptation for Personalized Impaired Speech Recognition
语音识别 | 7.5/10
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Opening the Design Space: Two Years of Performance with Intelligent Musical Instruments
音乐生成 | 6.5/10
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ICLAD: In-Context Learning with Comparison-Guidance for Audio Deepfake Detection
本文针对音频深度伪造检测模型在真实场景（in-the-wild）中泛化能力差的核心问题，提出了一种名为ICLAD的全新范式。该框架利用音频语言模型（ALM）的上下文学习能力，实现了无需训练的快速适应。其核心是创新的**成对比较推理**策略：在离线阶段，引导ALM为每个样本同时生成“真实”和“伪造”的