4 papers
Universal Semi-Supervised Domain Adaptation by Mitigating Common-Class Bias
Wenyu Zhang, Qingmu Liu, Felix Ong Wei Cong +2
Domain adaptation is a critical task in machine learning that aims to improve model performance on a target domain by leveraging knowledge from a related source domain. In this wor…
Mandarin Lombard Flavor Classification
Qingmu Liu, Yuhong Yang, Baifeng Li +3
The Lombard effect refers to individuals' unconscious modulation of vocal effort in response to variations in the ambient noise levels, intending to enhance speech intelligibility.…
Exploring Sentence Type Effects on the Lombard Effect and Intelligibility Enhancement: A Comparative Study of Natural and Grid Sentences
Hongyang Chen, Yuhong Yang, Zhongyuan Wang +3
This study explores how sentence types affect the Lombard effect and intelligibility enhancement, focusing on comparisons between natural and grid sentences. Using the Lombard Chin…
EMALG: An Enhanced Mandarin Lombard Grid Corpus with Meaningful Sentences
Baifeng Li, Qingmu Liu, Yuhong Yang +3
This study investigates the Lombard effect, where individuals adapt their speech in noisy environments. We introduce an enhanced Mandarin Lombard grid (EMALG) corpus with meaningfu…