ORCID as entered in ROS

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Zhang Q; Wickramasinghe B; Ambikairajah E; Sethu V; Li H, 2025, Should Audio Front-ends be Adaptive? Comparing Learnable and Adaptive Front-ends, http://dx.doi.org/10.48550/arxiv.2502.03260
Meng H; Breebaart J; Stoddard J; Sethu V; Ambikairajah E, 2024, Blind Estimation of Sub-band Acoustic Parameters from Ambisonics Recordings using Spectro-Spatial Covariance Features, http://arxiv.org/abs/2411.03172v2
Wu J; Dang T; Sethu V; Ambikairajah E, 2024, Dual-Constrained Dynamical Neural ODEs for Ambiguity-aware Continuous Emotion Prediction, http://dx.doi.org/10.48550/arxiv.2407.21344
Meng H; Zhang Q; Zhang X; Sethu V; Ambikairajah E, 2024, Binaural Selective Attention Model for Target Speaker Extraction, http://arxiv.org/abs/2406.12236v1
Zhang Q; Zhu H; Qian X; Ambikairajah E; Li H, 2024, An Exploration of Length Generalization in Transformer-Based Speech Enhancement, http://dx.doi.org/10.48550/arxiv.2406.11401
Zhang X; Zhang Q; Liu H; Xiao T; Qian X; Ahmed B; Ambikairajah E; Li H; Epps J, 2024, Mamba in Speech: Towards an Alternative to Self-Attention, http://dx.doi.org/10.48550/arxiv.2405.12609
Meng H; Sethu V; Ambikairajah E, 2024, What is Learnt by the LEArnable Front-end (LEAF)? Adapting Per-Channel Energy Normalisation (PCEN) to Noisy Conditions, http://dx.doi.org/10.21437/Interspeech.2023-1617
Zhang Q; Ge M; Zhu H; Ambikairajah E; Song Q; Ni Z; Li H, 2024, An Empirical Study on the Impact of Positional Encoding in Transformer-based Monaural Speech Enhancement, http://dx.doi.org/10.48550/arxiv.2401.09686
Dang T; Sethu V; Ambikairajah E; Epps J; Li H, 2021, Joint Spatio-Temporal Discretisation of Nonlinear Active Cochlear Models, http://dx.doi.org/10.48550/arxiv.2108.05993
Wu J; Dang T; Sethu V; Ambikairajah E, 2021, A Novel Markovian Framework for Integrating Absolute and Relative Ordinal Emotion Information, http://dx.doi.org/10.48550/arxiv.2108.04605
Pan Z; Chua Y; Wu J; Zhang M; Li H; Ambikairajah E, 2019, An efficient and perceptually motivated auditory neural encoding and decoding algorithm for spiking neural networks, http://dx.doi.org/10.48550/arxiv.1909.01302