4 accepted papers
Self-supervised representation learning approaches have grown in popularity due to the ability to train models on large amounts of unlabeled data and have demonstrated success in diverse fields such as natural language processing, computer vision, and speech. Previous self-supervised work in the spe…
The distinct cough sounds produced by a variety of respiratory diseases suggest the potential for the development of a new class of audio bio-markers for the detection of COVID-19. Accurate audio biomarker-based COVID-19 tests would be inexpensive, readily scalable, and non-invasive. Audio biomarker…
Dysarthria is a condition where people experience a reduction in speech intelligibility due to a neuromotor disorder. Previous works in dysarthric speech recognition have focused on accurate recognition of words encountered in training data. Due to the rarity of dysarthria in the general population,…
The ability to identify speech with similar emotional content is valuable to many applications, including speech retrieval, surveillance, and emotional speech synthesis. While current formulations in speech emotion recognition based on classification or regression are not appropriate for this task,…