25 citations · 41 across the 6 of their papers we have counts for
6 papers
EEG decoding with conditional identification information
Pengfei Sun, Jorg De Winne, Paul Devos +1
Decoding EEG signals is crucial for unraveling human brain and advancing brain-computer interfaces. Traditional machine learning algorithms have been hindered by the high noise lev…
AI-based soundscape analysis: Jointly identifying sound sources and predicting annoyance
Yuanbo Hou, Qiaoqiao Ren, Huizhong Zhang +4
Soundscape studies typically attempt to capture the perception and understanding of sonic environments by surveying users. However, for long-term monitoring or assessing interventi…
Audio Event-Relational Graph Representation Learning for Acoustic Scene Classification
Yuanbo Hou, Siyang Song, Chuang Yu +2
Most deep learning-based acoustic scene classification (ASC) approaches identify scenes based on acoustic features converted from audio clips containing mixed information entangled…
Joint Prediction of Audio Event and Annoyance Rating in an Urban Soundscape by Hierarchical Graph Representation Learning
Yuanbo Hou, Siyang Song, Cheng Luo +6
Sound events in daily life carry rich information about the objective world. The composition of these sounds affects the mood of people in a soundscape. Most previous approaches on…
Adaptive Axonal Delays in feedforward spiking neural networks for accurate spoken word recognition
Pengfei Sun, Ehsan Eqlimi, Yansong Chua +2
Spiking neural networks (SNN) are a promising research avenue for building accurate and efficient automatic speech recognition systems. Recent advances in audio-to-spike encoding a…
Audio-visual scene classification via contrastive event-object alignment and semantic-based fusion
Yuanbo Hou, Bo Kang, Dick Botteldooren
Previous works on scene classification are mainly based on audio or visual signals, while humans perceive the environmental scenes through multiple senses. Recent studies on audio-…