4 accepted papers
Speech emotion recognition (SER) is a key technology to enable more natural human-machine communication. However, SER has long suffered from a lack of public large-scale labeled datasets. To circumvent this problem, we investigate how unsupervised representation learning on unlabeled datasets can be…
We propose a semi-supervised learning method to improve classification performance in scenarios with limited labeled data. We employ adaptation strategies such as entropy-filtering and self-training, and show that our method achieves up to 17.2% relative improvement in UAR for a multi-class problem.…
Negative emotional arousal during conflict has been related to negative outcomes in romantic relationships and degraded quality of family life. Despite its extensive study in psychology, it is still challenging to quantify emotional arousal in a meaningful way with objective indices beyond tradition…
The study of speech pathology involves evaluation and treatment of speech production related disorders affecting phonation, fluency, intonation and aeromechanical components of respiration. Recently, speech pathology has garnered special interest amongst machine learning and signal processing (ML-SP…