| An investigation of annotation delay compensation and output-associative fusion for multimodal continuous emotion prediction Z Huang, T Dang, N Cummins, B Stasak, P Le, V Sethu, J Epps Proceedings of the 5th International Workshop on Audio/Visual Emotion …, 2015 | 87 | 2015 |
| Sounds of COVID-19: exploring realistic performance of audio-based digital testing J Han, T Xia, D Spathis, E Bondareva, C Brown, J Chauhan, T Dang, ... NPJ digital medicine 5 (1), 16, 2022 | 59 | 2022 |
| COVID-19 sounds: a large-scale audio dataset for digital respiratory screening T Xia, D Spathis, J Ch, A Grammenos, J Han, A Hasthanasombat, ... Thirty-fifth conference on neural information processing systems datasets …, 2021 | 58* | 2021 |
| Investigating word affect features and fusion of probabilistic predictions incorporating uncertainty in AVEC 2017 T Dang, B Stasak, Z Huang, S Jayawardena, M Atcheson, M Hayat, P Le, ... Proceedings of the 7th annual workshop on audio/visual emotion challenge, 27-35, 2017 | 52 | 2017 |
| Staircase regression in OA RVM, data selection and gender dependency in AVEC 2016 Z Huang, B Stasak, T Dang, K Wataraka Gamage, P Le, V Sethu, J Epps Proceedings of the 6th International Workshop on Audio/Visual Emotion …, 2016 | 36 | 2016 |
| An Investigation of Emotion Prediction Uncertainty Using Gaussian Mixture Regression. T Dang, V Sethu, J Epps, E Ambikairajah INTERSPEECH, 1248-1252, 2017 | 28 | 2017 |
| Uncertainty-aware COVID-19 detection from imbalanced sound data T Xia, J Han, L Qendro, T Dang, C Mascolo INTERSPEECH 2021, 2021 | 25 | 2021 |
| Exploring longitudinal cough, breath, and voice data for COVID-19 progression prediction via sequential deep learning: model development and validation T Dang, J Han, T Xia, D Spathis, E Bondareva, C Siegele-Brown, ... Journal of medical Internet research 24 (6), e37004, 2022 | 18* | 2022 |
| Speech-based continuous emotion prediction by learning perception responses related to salient events: A study based on vocal affect bursts and cross-cultural affect in AVEC 2018 K Wataraka Gamage, T Dang, V Sethu, J Epps, E Ambikairajah Proceedings of the 2018 on Audio/Visual Emotion Challenge and Workshop, 47-55, 2018 | 16 | 2018 |
| Dynamic multi-rater Gaussian Mixture Regression incorporating temporal dependencies of emotion uncertainty using kalman filters T Dang, V Sethu, E Ambikairajah ICASSP 2018, 2018 | 15 | 2018 |
| hEARt: Motion-resilient Heart Rate Monitoring with In-ear Microphones KJ Butkow, T Dang, A Ferlini, D Ma, C Mascolo 2023 IEEE International Conference on Pervasive Computing and Communications …, 2023 | 10* | 2023 |
| Speech Based Emotion Prediction: Can a Linear Model Work? A Ouyang, T Dang, V Sethu, E Ambikairajah Interspeech 2019, 2019 | 10 | 2019 |
| Factor Analysis Based Speaker Normalisation for Continuous Emotion Prediction. T Dang, V Sethu, E Ambikairajah INTERSPEECH, 913-917, 2016 | 10 | 2016 |
| A Novel Markovian Framework for Integrating Absolute and Relative Ordinal Emotion Information J Wu, T Dang, V Sethu, E Ambikairajah IEEE Transactions on Affective Computing, 2022 | 5 | 2022 |
| Multimodal affect models: An investigation of relative salience of audio and visual cues for emotion prediction J Wu, T Dang, V Sethu, E Ambikairajah Frontiers in Computer Science 3, 767767, 2021 | 3 | 2021 |
| Compensation Techniques for Speaker Variability in Continuous Emotion Prediction T Dang, V Sethu, E Ambikairajah IEEE Transactions on Affective Computing 12 (2), 439-452, 2018 | 3 | 2018 |
| A Novel Sequential Monte Carlo Framework for Predicting Ambiguous Emotion States J Wu, T Dang, V Sethu, E Ambikairajah ICASSP 2022-2022 IEEE International Conference on Acoustics, Speech and …, 2022 | 2 | 2022 |
| Exploring Semi-supervised Learning for Audio-based COVID-19 Detection using FixMatch T Dang, T Quinnell, C Mascolo Proc. Interspeech 2022, 2468-2472, 2022 | 2 | 2022 |
| A Novel Bag-of-Optimised-Clusters Front-End for Speech based Continuous Emotion Prediction D Bose, T Dang, V Sethu, EAS Fernando ACII, 2019 | 2 | 2019 |
| Conditional Neural ODE Processes for Individual Disease Progression Forecasting: A Case Study on COVID-19 T Dang, J Han, T Xia, E Bondareva, C Siegele-Brown, J Chauhan, ... ACM Conference on Knowledge Discovery & Data Mining (KDD 2023), 2023 | 1 | 2023 |
Vidhyasaharan SethuSenior Lecturer, The University of New South WalesVerified email at unsw.edu.au
