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ICASSP 2024 Papers: A complete collection of influential and exciting research papers from the ICASSP 2024 conference. Explore the latest advancements in acoustics, speech and signal processing. Code included. ⭐ the repository to support the advancement of audio and signal processing!
Tip
Online version of the ICASSP 2024 Conference Technical Program, which lists all accepted full papers along with their presentation mode and time.
Other collections of the best AI conferences
Important
Conference table will be up to date all the time.
Note
Contributions to improve the completeness of this list are greatly appreciated. If you come across any overlooked papers, please feel free to create pull requests, open issues or contact me via email. Your participation is crucial to making this repository even better.
Section | Papers | |||
---|---|---|---|---|
Main | ||||
Audio-Visual Speech Processing | ||||
Vision and Language | ||||
Acoustic Signal Processing | ||||
Deep Learning Techniques | ||||
Speech Enhancement and Separation - Diffusion and other Probabilistic Models | ||||
ASPS Lecture | ||||
Distributed and Federated Learning | ||||
Transfer Learning | ||||
Voice Conversion | ||||
Graph Neural Networks | ||||
Language Resources, Metrics and Systems | ||||
Watermarking and Data Hiding | ||||
Signal and Information Processing over Graphs | ||||
Integrated Sensing and Communications | ||||
Audio Events Detection and Classification; Music Information Retrieval | ||||
Language Understanding and Computational Semantics - NLP Tasks | ||||
Physiological and Wearable Signal Processing | ||||
Speech Enhancement; Music Information Retrieval | ||||
Multimodal Medical Image Fusion and Analysis | ||||
Sparse/Low-Dimensional Signal Processing | ||||
Robust and Sustainable Machine Learning | ||||
Machine Learning for Image and Video Processing | ||||
Deep Learning Generalization | ||||
Distributed Processing and Federated Learning | ||||
Biological Image Analysis | ||||
Learning from Multimodal Data | ||||
Biometrics | ||||
Detection and Classification | ||||
Multimedia Coding | ||||
Anonymisation, Data Privacy and Hiding | ||||
Quality Assessment and Anomaly Detection | ||||
Signal Filtering, Reconstruction, Restoration and Enhancement | ||||
Speech Emotion Recognition and Analysis | ||||
Deep Generative Models | ||||
Context and LLM Speech Recognition | ||||
Music Information Retrieval | ||||
Multimodal Processing: Vision + Language | ||||
Environmental Sound Synthesis and Generation | ||||
Biomedical and Biological Image Processing | ||||
DoA Estimation | ||||
Tracking | ||||
Machine Learning for Communications | ||||
Image and Video Processing for Watermarking and Security | ||||
Self-Supervised Learning for Speech Processing | ||||
Deep Learning for Image and Video Processing | ||||
Image, Video, and 3D Content Generation | ||||
Classification of Acoustic Scenes and Events | ||||
Reinforcement Learning | ||||
Subspace and Manifold Learning | ||||
Active Noise Control and Echo Cancellation; Source Separation | ||||
Machine Learning, Detection and Classification | ||||
Machine Learning for Audio, Speech and Music Processing | ||||
Multimedia Generation and Synthesis | ||||
Medical Image Detection and Segmentation | ||||
Multimedia Forensics and Cybersecurity | ||||
Estimation Theory and Methods | ||||
Emerging Methods for Biomedical Image and Signal Processing | ||||
Text to Speech Generation | ||||
Audio Classification, Detection and Localization | ||||
Self-Supervised and Semi-Supervised Learning | ||||
Multichannel/Multimodal Speech Recognition | ||||
Speaker Verification | ||||
Speaker Diarization | ||||
Adversarial Machine Learning | ||||
Machine Learning Methods for Language | ||||
SPED: Signal Processing Education | ||||
Multimedia Quality of Experience | ||||
Domain-Enriched Learning for Medical Image Processing | ||||
Speech Enhancement and Separation | ||||
Image Denoising | ||||
ASPS Poster | ||||
ASR - New Algorithms and Approaches | ||||
Data Mining and Big Data | ||||
Language Understanding and Computational Semantics - Machine Learning | ||||
Explainable and Interpretable Machine Learning | ||||
Neuroimaging and Brain/Human-Computer Interfaces | ||||
Localization, DOA Estimation, Spatial Audio Recording and Reproduction | ||||
Perception and Processing for Autonomous Systems and Applications | ||||
Computational Imaging | ||||
Audio and Speech Quality and Intelligibility Measures; Music Analysis | ||||
Medical Image Formation, Reconstruction and Restoration | ||||
Audio and Speech Source Separation | ||||
Text-based Customization for Speech-to-Text | ||||
Deep Learning Models | ||||
Next-Gen Communication Systems | ||||
Image Restoration | ||||
Robustness and Trustworthy Machine Learning | ||||
Signal Processing over Networks | ||||
3D Understanding | ||||
Compressed Sensing and Machine Learning for Multi-Sensor Systems | ||||
LIMMITS: Multi-Speaker, Multi-Lingual Indic TTS with Voice Cloning | ||||
Natural Language Processing for Speech-to-Text | ||||
Resource Constrained Acoustic and Language Modeling | ||||
Dereverberation and RIR Estimation; Speech Enhancement and Restoration | ||||
Image/Video Super-Resolution | ||||
Matrix Factorization and Source Separation | ||||
Beamforming for Audio and Speech; Music Signal Analysis, Processing and Synthesis | ||||
Summarization, Retrieval and Language Learning | ||||
Sequential Learning and Sequential Decision Methods | ||||
MIMO and Massive MIMO Communication Systems | ||||
Multimodal Emotion/Sentiment Analysis | ||||
Human Understanding | ||||
Image and Video Synthesis | ||||
MIMO and High-Frequency Communications | ||||
Image and Video Super-Resolution | ||||
Spatial Audio Recording and Reproduction | ||||
Audio Signal Restoration and Speech Enhancement | ||||
Discourse and Dialog | ||||
Bayesian Signal Processing | ||||
Pattern Recognition and Classification | ||||
Key Word Spotting | ||||
Speech Analysis - Pitch, Spectrum and Voice Disorders | ||||
Grand Challenge on Hyperspectral Skin Vision | ||||
Robust Speech Recognition and Adaptation | ||||
Speech Analysis and Language Disorder Analysis | ||||
Aspects in Image/Video Processing and Analysis | ||||
DoA Estimation and Source Localization | ||||
Multimodal Processing of Language | ||||
Source separation; Music analysis | ||||
Machine Learning for Time Series Analysis | ||||
Multimedia Search and Retrieval | ||||
Anomaly Detection; Sound Event Detection and Localization | ||||
Acoustic Array and Signal Processing | ||||
Music Signal Analysis and Processing | Will soon be added | |||
Language Understanding and Computational Semantics - Language Models | ||||
Deep Learning Theory | ||||
Anti-Spoofing | ||||
Pose, Gesture, and Action in Multimedia | ||||
Sampling Theory, Compressed and Non-Uniform Sampling | ||||
MIMO and Massive MIMO Systems | ||||
Multimodal and Emerging Medical Signal Analysis | ||||
The RF Signal Separation Challenge | ||||
Signal Processing for Communications | ||||
Audio and Speech Modeling, Coding and Transmission; Spatial Audio Recording and Reproduction | ||||
Voice Conversion: Singing, Accent and Emotion | ||||
Other Machine Learning Applications | ||||
Speaker Recognition and Anonymization | ||||
Feature Extraction Selection and Learning | ||||
Music Information Retrieval; Quality and Intelligibility Measures | ||||
Learning Theory and Performance Bound | ||||
Human-Centric Multimedia | ||||
Multilingual Speech Recognition and Identification | ||||
Image Recognition and Detection | ||||
Signal Processing over Graphs and Networks | ||||
End-to-End Modeling for Automatic Speech Recognition | ||||
Segmentation, Tagging, and Parsing of Language | ||||
Detection | ||||
Audio-Language Processing and Audio Captioning | ||||
Action Recognition | ||||
Image, Video and Other Applications | ||||
Multimodal Information Based Speech Processing (MISP) | ||||
Next-Gen Communications and PHY Security | ||||
Network and System Security | ||||
Target Source Extraction; Active Noise Control, Echo Reduction and Feedback Reduction | ||||
Machine Translation for Spoken and Written Language | ||||
Sound Events Detection, Description and Generation | ||||
Applied Cryptography | ||||
Machine/Deep Learning Methodologies for Multimedia | ||||
Speech Separation and Extraction | ||||
Signal Processing and Machine Learning for Communications | ||||
Audio Coding | ||||
Active Noise Control and Echo Cancellation | ||||
Bayesian Machine Learning | ||||
Advancing the Frontiers of Deep Learning for Low-Dose 3D Cone-Beam CT Reconstruction | ||||
Bioacoustics and Medical Acoustics; Audio Security | ||||
Acoustic Modeling for Automatic Speech Recognition | ||||
Multimodal Processing of Speech | ||||
IFS General | ||||
3D Image and Video Processing and Analysis | ||||
Deep Learning Training Methods | ||||
Key Word Spotting and Acoustic Event Detection | ||||
Coding, Information Theory, and Applications of Signal Processing for Communications | ||||
Speech Analysis | ||||
Music Separation; Audio for Multimedia and Audio Processing Systems | ||||
Machine Learning for Communications and Wireless Networks | ||||
Image and Video Coding/Compression | ||||
Bioinformatics and Biomedical Signal Processing | ||||
Audio-Visual Speech/Intent Recognition | ||||
Multimodal Clustering, Segmentation, and Summarization | ||||
Learning Theory and Methods | ||||
SP Cadenza Challenge: Music Demixing/Remixing for Hearing Aids | ||||
Radar Signal Processing | ||||
Biological and Medical Signal and Image Processing | ||||
Anti-Spoofing and Speaker Embedding | ||||
Speech Enhancement; Dereverberation and RIR Estimation | ||||
Segmentation | ||||
3D Generation | ||||
Multimedia Forensics | ||||
Speech Signal Improvement Challenge | ||||
Audio Deep Packet Loss Concealment Grand Challenge | ||||
Signal Processing Theory and Methods Journal Papers | ||||
Multi-Sensor and Multichannel Signal Processing | ||||
Array Processing and Beamforming | ||||
Sound Event Classification and Generation; Active Noise Control, Echo Reduction and Feedback Reduction | ||||
Deep Learning Fairness and Privacy | ||||
Sparsity and Low-Rank Models | ||||
Optimization Methods for Signal Processing | ||||
Multimodal Processing | ||||
Show and Tell Demos | ||||
Special Session | ||||
Model based Machine Learning for Wireless Communications and Sensing | Will soon be added | |||
Exploiting Diversities in Advanced Array Systems: New Applications and Trends | ||||
Generative Semantic Communication: How Generative Models Enhance Semantic Communications | ||||
Quantum Machine Learning Algorithms and Applications on NISQ Devices | ||||
Robust Reconstruction Methods in Computational Imaging | ||||
Graphical Inference and Modeling in Dynamical Systems | ||||
Advancements in Integrated Sensing and Communication for Next-Generation Wireless Networks | ||||
Signal and Graph Processing for Autonomous Agents | ||||
Next-Generation Wi-Fi Sensing | ||||
Signal Processing Theory for Covert Communication and Cybersecurity | ||||
In-Context Learning Methods for Speech and Spoken Language Processing | ||||
Topological Signal Processing over Higher-Order Networks | ||||
Deepfakes and AI-Generated Content (AIGC) Detection and Forensics: Recent Advances | ||||
Recent Advances in AI-Powered Visual Computing and Multimodal Signal Processing for Metaverse Era | ||||
Algorithm-Hardware Co-Design of Neuromorphic Solutions for Signal Processing Applications | ||||
Automotive Radar Signal Processing for Autonomous Driving | ||||
Learning with Incomplete Medical Data | ||||
Signal Processing and Machine Learning for Collective Intelligence | ||||
Variational Inference and Approximate Bayesian Techniques | ||||
Efficient Modeling of Long Sequences with Applications to Speech and Audio | ||||
Decentralized Learning with Resource-Constrained Communication | ||||
Localization and Sensing based on Signals from Terrestrial and Non-Terrestrial Networks | ||||
Signal Processing and Machine Learning for Understanding Brain Dynamics |