Search Results for author:
Found 10 papers, 6 papers with code
EEG decoding with conditional identification information
Decoding EEG signals is crucial for unraveling human brain and advancing brain-computer interfaces.
Multi-level graph learning for audio event classification and human-perceived annoyance rating prediction
Specifically, this paper proposes a lightweight multi-level graph learning (MLGL) based on local and global semantic graphs to simultaneously perform audio event classification (AEC) and human annoyance rating prediction (ARP).
AI-based soundscape analysis: Jointly identifying sound sources and predicting annoyance
(4) Generalization tests show that the proposed model's ARP in the presence of model-unknown sound sources is consistent with expert expectations and can explain previous findings from the literature on sound-scape augmentation.
Delayed Memory Unit: Modelling Temporal Dependency Through Delay Gate
Recurrent Neural Networks (RNNs) are renowned for their adeptness in modeling temporal dependencies, a trait that has driven their widespread adoption for sequential data processing.
Audio Event-Relational Graph Representation Learning for Acoustic Scene Classification
The results show the feasibility of recognizing diverse acoustic scenes based on the audio event-relational graph.
Acoustic Scene Classification
Graph Representation Learning
+1
Joint Prediction of Audio Event and Annoyance Rating in an Urban Soundscape by Hierarchical Graph Representation Learning
Sound events in daily life carry rich information about the objective world.
Adaptive Axonal Delays in feedforward spiking neural networks for accurate spoken word recognition
Spiking neural networks (SNN) are a promising research avenue for building accurate and efficient automatic speech recognition systems.
Ranked #2 on
Audio Classification
on SHD
Multi-dimensional Edge-based Audio Event Relational Graph Representation Learning for Acoustic Scene Classification
Experiments on a polyphonic acoustic scene dataset show that the proposed ERGL achieves competitive performance on ASC by using only a limited number of embeddings of audio events without any data augmentations.
Acoustic Scene Classification
Graph Representation Learning
+1
Axonal Delay As a Short-Term Memory for Feed Forward Deep Spiking Neural Networks
The information of spiking neural networks (SNNs) are propagated between the adjacent biological neuron by spikes, which provides a computing paradigm with the promise of simulating the human brain.
Rule-embedded network for audio-visual voice activity detection in live musical video streams
Detecting anchor's voice in live musical streams is an important preprocessing for music and speech signal processing.
Sound Multimedia Audio and Speech Processing
