An ensemble learning-enhanced multitask learning method for continuous affect recognition from facial images
Continuous affect recognition from facial images aims to estimate the values of multiple
affective dimensions from a facial image sequence. To leverage relevant information …
affective dimensions from a facial image sequence. To leverage relevant information …
The ambiguous world of emotion representation
Artificial intelligence and machine learning systems have demonstrated huge improvements
and human-level parity in a range of activities, including speech recognition, face …
and human-level parity in a range of activities, including speech recognition, face …
Estimating the uncertainty in emotion attributes using deep evidential regression
W Wu, C Zhang, PC Woodland - arXiv preprint arXiv:2306.06760, 2023 - arxiv.org
In automatic emotion recognition (AER), labels assigned by different human annotators to
the same utterance are often inconsistent due to the inherent complexity of emotion and the …
the same utterance are often inconsistent due to the inherent complexity of emotion and the …
Dimensional affect uncertainty modelling for apparent personality recognition
MK Tellamekala, T Giesbrecht… - IEEE Transactions on …, 2022 - ieeexplore.ieee.org
Despite achieving impressive performance, dimensional affect or emotion recognition from
faces is largely based on uncertainty-unaware models that predict only point estimates …
faces is largely based on uncertainty-unaware models that predict only point estimates …
Estimating the uncertainty in emotion class labels with utterance-specific Dirichlet priors
Emotion recognition is a key attribute for artificial intelligence systems that need to naturally
interact with humans. However, the task definition is still an open problem due to the …
interact with humans. However, the task definition is still an open problem due to the …
A bayesian filtering framework for continuous affect recognition from facial images
Continuous affective state estimation from facial information is a task which requires the
prediction of time series of emotional state outputs from a facial image sequence. Modeling …
prediction of time series of emotional state outputs from a facial image sequence. Modeling …
Exploring perception uncertainty for emotion recognition in dyadic conversation and music listening
Predicting emotions automatically is an active field of research in affective computing.
Considering the property of the individual's subjectivity, the label of an emotional instance is …
Considering the property of the individual's subjectivity, the label of an emotional instance is …
End-to-end label uncertainty modeling in speech emotion recognition using bayesian neural networks and label distribution learning
NR Prabhu, N Lehmann-Willenbrock… - IEEE Transactions on …, 2023 - ieeexplore.ieee.org
To train machine learning algorithms to predict emotional expressions in terms of arousal
and valence, annotated datasets are needed. However, as different people perceive others' …
and valence, annotated datasets are needed. However, as different people perceive others' …
Dual-Constrained Dynamical Neural ODEs for Ambiguity-aware Continuous Emotion Prediction
There has been a significant focus on modelling emotion ambiguity in recent years, with
advancements made in representing emotions as distributions to capture ambiguity …
advancements made in representing emotions as distributions to capture ambiguity …
Apparent personality recognition from uncertainty-aware facial emotion predictions using conditional latent variable models
MK Tellamekala, T Giesbrecht… - 2021 16th IEEE …, 2021 - ieeexplore.ieee.org
We propose two key ideas to improve the performance of apparent personality traits
estimation from face videos: 1. using dimensional emotion predictions fused with face image …
estimation from face videos: 1. using dimensional emotion predictions fused with face image …