Latest Research in Audio and Speech Processing
22 research papers · 2026 median publication year
Top Research Topics in Audio and Speech Processing
- Sound — 10 papers
- Audio and Speech Processing — 5 papers
- Music and Audio Processing — 3 papers
- Music Technology and Sound Studies — 1 papers
- Speech and Audio Processing — 1 papers
- Signal Processing — 1 papers
- Animal Vocal Communication and Behavior — 1 papers
Highest-Cited Papers
- Intelligent music creation enhanced by graph neural networks and federated learning
- A Gated Multi-Head Network with Semantic–Spatial Features for Sound Event Localization and Detection
- Steering dense music retrieval with open-vocabulary concept discovery
- A study on vocal style recognition using a multiscale time frequency feature fusion algorithm
- EG-VAE: A Unified Framework for Electric Guitar Tone Transfer and Removal
- AudioScape-TTA: A Structured Soundscape Benchmark for Fine-Grained Text-to-Audio Evaluation
- PhaseCoder: Microphone Geometry-Agnostic Spatial Audio Understanding for Multimodal LLMs
- Can Foundation Models Hear What Made That Sound? A Tiered Benchmark of Audio-Language Models and Traditional Classifiers for Closed-Set Sound Source Identification
- SGAD: A State-Guided Adaptive Decision Framework for Robust EEG-Based Auditory Attention Switch Decoding
- Music Restoration via Latent Operator Optimization and Diffusion Model Priors
- Anomalous Sound Detection Meets Noise-Aware Self-Supervised Learning
- CSG ‐Net: A Causal‐Aware Structural Graph Network for Multimodal Music Emotion Recognition
- Contrastive ecoacoustic indices: Large‐scale global soundscape characterization with contrastive inference
- CrowdioSet and PaRIRset: Two Datasets Towards Live Music Source Separation
- VocalRender: Score-Native Singing Voice Synthesis for Real-World Composition
- Learning to Predict Performance-induced Emotion Differences in Classical Piano Music
- Spacing Out: On the Reliability of Binaural Music Source Separation Metrics
- Emotion-aware Multimodal Music Recommendation via Semantic Image-audio Alignment
- Music-Source-Separation-Training (MSST): A Unified Framework for Training and Evaluating Music Demixing Models
- Improved Monitoring of Honey bee Colony Strength via Audio IoT Sensors, Modulation Tensorgrams and Recurrent Neural Networks