5 accepted papers
Paraphrasing of offensive content is a better alternative to content removal and helps improve civility in a communication environment. Supervised paraphrasers; however, rely heavily on large quantities of labelled data to help preserve meaning and intent. They also often retain a large portion of t…
This paper explores the use of multi-view features and their discriminative transforms in a convolutional deep neural network (CNN) architecture for a continuous large vocabulary speech recognition task. Mel-filterbank energies and perceptually motivated forced damped oscillator coefficient (DOC) fe…
Articulatory information can effectively model variability in speech and can improve speech recognition performance under varying acoustic conditions. Learning speaker-independent articulatory models has always been challenging, as speaker-specific information in the articulatory and acoustic spaces…
Speech recognition in varying background conditions is a challenging problem. Acoustic condition mismatch between training and evaluation data can significantly reduce recognition performance. For mismatched conditions, data-adaptation techniques are typically found to be useful, as they expose the…
Research on detecting depression from speech has advanced in recent years, but most work has focused on the analysis of one corpus at a time. Given that clinical corpora are typically small, it is important to explore approaches that generalize across corpora and that could ultimately be adapted to…