Beyond the Labels: Unveiling Text-Dependency in Paralinguistic Speech Recognition Datasets

arXiv:2403.07767v1 Announce Type: cross
Abstract: Paralinguistic traits like cognitive load and emotion are increasingly recognized as pivotal areas in speech recognition research, often examined through specialized datasets like CLSE and IEMOCAP. However, the integrity of these datasets is seldom scrutinized for text-dependency. This paper critically evaluates the prevalent assumption that machine learning models trained on such datasets genuinely learn to identify paralinguistic traits, rather than merely capturing lexical features. By examining the lexical overlap in these datasets and testing the …

abstract arxiv beyond cognitive cs.lg datasets eess.as eess.sp emotion however integrity labels paper pivotal recognition research speech speech recognition text through type