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Data Challenges

(with available data challenges)
Current Challenges


Audio and Acoustic Signal Processing

2024

Someone with a hearing loss is listening to music via their hearing aids or headphones. The challenge is to develop a signal processing system that allows a personalised rebalancing of the music to improve the listening experience, for example by amplifying the vocals relative to the sound of the band. 

PLC is an important part of audio telecommunications technology and codec development, and methods for performing PLC using machine learning approaches are now becoming viable for practical use.

Supported by the SPS Challenge Program.

This challenge addresses the global problem of hearing loss, which will affect 1 in 10 people by 2050. Hearing loss can create many issues with music: quieter passages being inaudible; poor and anomalous pitch perception; and difficulties identifying and picking out instruments and lyrics.

Supported by the SPS Challenge Program.

Personalised Head-Related Transfer Functions (HRTFs) have been shown to enhance auditory localization and immersion in mixed realities. However, relevant issues, such as the accurate acquisition of user-specific anatomical data, efficient simulation algorithms, and effective user validation, do not converge into a common and internationally recognized benchmark for evaluating HRTFs.



Bio Imaging and Signal Processing

2024

Various neuroimaging techniques can be used to investigate how the brain processes sound. Electroencephalography (EEG) is popular because it is relatively easy to conduct and has a high temporal resolution. Besides fundamental neuroscience research, EEG-based measures of auditory processing in the brain are also helpful in detecting or diagnosing potential hearing loss. 

The  2nd e-Prevention challenge (https://robotics.ntua.gr/icassp2024-eprevention-spgc/) aims to stimulate innovative research on the prediction and identification of mental health relapses via the analysis and processing of the digital phenotype of patients in the psychotic spectrum.

Introducing ICASSP 2024 SPGC competition aiming at reconstructing skin spectral reflectance in the visible (VIS) and near-infrared (NIR) spectral range from RGB images captured by everyday cameras, offering a transformative approach for cosmetic and beauty applications. 

Supported by the SPS Challenge Program

The George B. Moody PhysioNet Challenges are annual competitions that invite participants to develop automated approaches for addressing important physiological and clinical problems. The 2024 Challenge invites teams to develop algorithms for digitizing and classifying electrocardiograms (ECGs) captured from images or paper printouts. 

Auto-WCEBleedGen Challenge is an second version of a previous challenge that focused on automatic detection and classification of bleeding and non-bleeding frames. 

The proposed challenge seeks to push the limits of deep learning algorithms for 3D cone beam computed tomography (CBCT) reconstruction from low-dose projection data (sinogram). 



Applied Signal Processing Systems

2024

Supported by the SPS Challenge Program.

Accurate analysis of liver vasculature in three dimensions (3D) is essential for a variety of medical procedures including computer-aided diagnosis, treatment planning, or pre-operative planning of hepatic diseases.

Supported by the SPS Challenge Program

The George B. Moody PhysioNet Challenges are annual competitions that invite participants to develop automated approaches for addressing important physiological and clinical problems. The 2024 Challenge invites teams to develop algorithms for digitizing and classifying electrocardiograms (ECGs) captured from images or paper printouts. 



Image, Video, and Multidimensional Signal Processing

2024

Omnidirectional visual content, commonly referred to as 360-degree images and videos, has garnered significant interest in both academia and industry, establishing itself as the primary media modality for VR/XR applications. 

Video compression standards rely heavily on eliminating spatial and temporal redundancy within and across video frames. Intra-frame encoding targets redundancy within blocks of a single video frame, whereas inter-frame coding focuses on removing redundancy between the current frame and its reference frames.

Introducing ICASSP 2024 SPGC competition aiming at reconstructing skin spectral reflectance in the visible (VIS) and near-infrared (NIR) spectral range from RGB images captured by everyday cameras, offering a transformative approach for cosmetic and beauty applications. 

Supported by the SPS Challenge Program.

Accurate analysis of liver vasculature in three dimensions (3D) is essential for a variety of medical procedures including computer-aided diagnosis, treatment planning, or pre-operative planning of hepatic diseases.

Supported by the SPS Challenge Program

The George B. Moody PhysioNet Challenges are annual competitions that invite participants to develop automated approaches for addressing important physiological and clinical problems. The 2024 Challenge invites teams to develop algorithms for digitizing and classifying electrocardiograms (ECGs) captured from images or paper printouts. 

Speech-enabled systems often experience performance degradation in real-world scenarios, primarily due to adverse acoustic conditions and interactions among multiple speakers. Enhancing the front-end speech processing technology is vital for improving the performance of the back-end systems. 

View synthesis is a task of generating novel views of a scene/object from a given set of input views. It is a challenging and important problem in computer vision and graphics, with significant applications in virtual and augmented reality, 3D reconstruction, video editing, and more.



Machine Learning for Signal Processing

2024

PLC is an important part of audio telecommunications technology and codec development, and methods for performing PLC using machine learning approaches are now becoming viable for practical use.

Supported by the SPS Challenge Program.

This challenge addresses the global problem of hearing loss, which will affect 1 in 10 people by 2050. Hearing loss can create many issues with music: quieter passages being inaudible; poor and anomalous pitch perception; and difficulties identifying and picking out instruments and lyrics.

This challenge will require developing an engine for signal separation  of radio-frequency (RF) waveforms. At inference time, a superposition of a signal of interest (SOI) and an interfering signal will be fed to the engine, which should recover the SOI by performing a sophisticated interference cancellation. 

Supported by the SPS Challenge Program.

Accurate analysis of liver vasculature in three dimensions (3D) is essential for a variety of medical procedures including computer-aided diagnosis, treatment planning, or pre-operative planning of hepatic diseases.

Supported by the SPS Challenge Program

The George B. Moody PhysioNet Challenges are annual competitions that invite participants to develop automated approaches for addressing important physiological and clinical problems. The 2024 Challenge invites teams to develop algorithms for digitizing and classifying electrocardiograms (ECGs) captured from images or paper printouts. 



Signal Processing for Communications and Networking

2024

This challenge will require developing an engine for signal separation  of radio-frequency (RF) waveforms. At inference time, a superposition of a signal of interest (SOI) and an interfering signal will be fed to the engine, which should recover the SOI by performing a sophisticated interference cancellation. 



Speech and Language Processing

2024

As cars become indispensable parts of human daily life, a safe and comfortable driving environment is more desirable. The traditional touch-based interaction in cockpit is easy to distract the drivers' attention, leading to inefficient operations and potential security risks. 

This challenge is the continuation of LIMMITS'23 (ICASSP 23 SPGC), it is aimed at making further progress in multi-speaker, multi-lingual TTS by extending the problem statement to voice cloning.  

The ICASSP 2024 Speech Signal Improvement Challenge is intended to stimulate research in the area of improving the speech signal quality in communication systems. The speech signal quality can be measured with SIG in ITU-T P.835 and is still a top issue in audio communication and conferencing systems.

Speech-enabled systems often experience performance degradation in real-world scenarios, primarily due to adverse acoustic conditions and interactions among multiple speakers. Enhancing the front-end speech processing technology is vital for improving the performance of the back-end systems. 

Past Challenges


Audio and Acoustic Signal Processing

2023

Verbal communication in noisy environments can be hard. Speech enhancement using head-worn microphone arrays, such as hearing aids or augmented reality devices offers the opportunity to make it easier. However, the highly dynamic nature of the listening situation presents some challenges.

The ICASSP 2023 Acoustic Echo Cancellation Challenge is intended to stimulate research in acoustic echo cancellation (AEC), which is an important area of speech enhancement and is still a top issue in audio communication. This is the fourth AEC challenge and it is enhanced by adding a second track for personalized acoustic echo cancellation, reducing the algorithmic latency to 20ms, and including a full-band version of AECMOS.

The L3DAS23 Challenge is aimed at encouraging and fostering collaborative research on machine learning for 3D audio signal processing, with a particular focus on 3D speech enhancement (SE) and 3D sound event localization and detection (SELD) in augmented reality applications.

2022

Associated SPS Event: IEEE ICASSP 2022 Grand Challenge

Over the last few years, the technology of speech synthesis and voice conversion has made significant improvement with the development of deep learning. The models can generate realistic and human-like speech. It is difficult for most people to distinguish the generated audio from the real. However, this technology also poses a great threat to the global political economy and social stability if some attackers and criminals misuse it with the intent to cause harm. 

Associated SPS Event: IEEE ICASSP 2022 Grand Challenge

Noise suppression has become more important than ever before due to the increasing use of voice interfaces for various applications. Given the millions of internet-connected devices being employed for audio/video calls, noise suppression is expected to be effective for all noise types chosen from daily-life scenarios.

Associated SPS Event: IEEE ICASSP 2022 Grand Challenge

The L3DAS22 Challenge aims at encouraging and fostering research on machine learning for 3D audio signal processing. 3D audio is gaining increasing interest in the machine learning community in recent years. The range of applications is incredibly wide, extending from virtual and real conferencing to autonomous driving, surveillance and many more.

Associated SPS Event: IEEE ICASSP 2022 Grand Challenge

The ICASSP 2022 Acoustic Echo Cancellation Challenge is intended to stimulate research in the area of acoustic echo cancellation (AEC), which is an important part of speech enhancement and still a top issue in audio communication and conferencing systems. 

Listening in noisy reverberant environments can be challenging. The recent emergence of hearable devices, such as smart headphones, smart glasses and virtual/augmented reality headsets, presents an opportunity for a new class of speech and acoustic signal processing algorithms which use multimodal sensor data to compensate for, or even exploit, changes in head orientation. 

2021

Associated SPS Event: IEEE ICASSP 2021 Grand Challenge

The ICASSP 2021 Acoustic Echo Cancellation Challenge is intended to stimulate research in the area of acoustic echo cancellation (AEC), which is an important part of speech enhancement and still a top issue in audio communication and conferencing systems. Many recent AEC studies report good performance on synthetic datasets where the train and test samples come from the same underlying distribution.

Associated SPS Event: IEEE ICASSP 2021 Grand Challenge

Text-to-speech (TTS) or speech synthesis has witnessed significant performance improvement with the help of deep learning. The latest advances in end-to-end text-to-speech paradigm and neural vocoder have enabled us to produce very realistic and natural-sounding synthetic speech reaching almost human-parity performance. But this amazing ability is still limited to the ideal scenarios with a large single-speaker less-expressive training set.

Associated SPS Event: IEEE ICASSP 2021 Grand Challenge

The ICASSP 2021 Deep Noise Suppression (DNS) challenge is designed to foster innovation in the field of noise suppression to achieve superior perceptual speech quality. We recently organized a DNS challenge special session at INTERSPEECH 2020. We open sourced training and test datasets for researchers to train their noise suppression models. We also open sourced a subjective evaluation framework and used the tool to evaluate and pick the final winners. Many researchers from academia and industry made significant contributions to push the field forward.

2019

The Interspeech 2019 Computational Paralinguistics ChallengE (ComParE) is an open Challenge dealing with states and traits of speakers as manifested in their speech signal’s properties.

DIHARD II is the second in a series of diarization challenges focusing on "hard" diarization; that is, speaker diarization for challenging recordings where there is an expectation that the current state-of-the-art will fare poorly.

2018

The IEEE AASP Challenge on acoustic source LOCalization And TrAcking (LOCATA) aims at providing researchers in source localization and tracking with a framework to objectively benchmark results against competing algorithms using a common, publicly released data corpus that encompasses a range of realistic scenarios in an enclosed acoustic environment. Data corresponding to the LOCATA challenge

2017

The IEEE Signal Processing Society announced the fourth edition of the Signal Processing Cup: a real-time beat tracking challenge. The beat is a salient periodicity in a music signal. It provides a fundamental unit of time and foundation for the temporal structure of the music. As Meinard Müller says (Fundamentals of Music Processing, Springer, 2015), “It is the beat that drives music forward and provides the temporal framework of a piece of music. Intuitively, the beat corresponds to the pulse a human taps along when listening to music.”

2016

The workshop aims to provide a venue for researchers working on computational analysis of sound events and scene analysis to present and discuss their results. We aim to bring together researchers from many different universities and companies with interest in the topic, and provide the opportunity for scientific exchange of ideas and opinions. The workshop is organized as a satellite event to the 2016 European Signal Processing Conference (EUSIPCO).

2014

The ACE Challenge was part of the programme of Challenges organised by the IEEE Audio and Acoustic Signal Processing Technical Committee. The aim of this challenge was to evaluate state-of-the-art algorithms for blind acoustic parameter estimation from speech and to promote the emerging area of research in this field. Participants will evaluate their algorithms for T60 and DRR estimation against the ‘ground truth’ values provided with the data-sets. Furthermore, they are expected to present the results in a paper describing the method used.

Recently, substantial progress has been made in the field of reverberant speech signal processing, including both single- and multi-channel de-reverberation techniques, and automatic speech recognition (ASR) techniques robust to reverberation. REVERB (REverberant Voice Enhancement and Recognition Benchmark) challenge that provides an opportunity to the researchers in the field to carry out a comprehensive evaluation of their methods based on a common database and on common evaluation metrics.

The challenge will consider the problem of distant multi-microphone conversational speech recognition in everyday home environments. Speech material was elicited using a dinner party scenario with efforts taken to capture data that is representative of natural conversational speech.

2013

The workshop aims to provide a venue for researchers working on computational analysis of sound events and scene analysis to present and discuss their results. We aim to bring together researchers from many different universities and companies with interest in the topic, and provide the opportunity for scientific exchange of ideas and opinions. 



Bio Imaging and Signal Processing

2023

The challenge will concern the analysis and processing of long-term continuous recordings of biosignals recorded from wearable sensors embedded in smartwatches, in order to extract high-level representations of the wearer’s activity and behavior for two downstream tasks: 1) Identification of the wearer of the smartwatch, and 2) Detection of relapses in patients in the psychotic spectrum. 

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