4 papers
Looking for Affect in Spontaneous Finnish Speech through Linguistic Interpretability
Kalle Lahtinen, Liisa Mustanoja, Okko Räsänen
Existing research on affect in speech has shown how acoustic surface characteristics and content-related linguistic aspects of speech both relate to perceived emotional arousal and…
Evaluating Interactive 2D Visualization as a Sample Selection Strategy for Biomedical Time-Series Data Annotation
Einari Vaaras, Manu Airaksinen, Okko Räsänen
Reliable machine-learning models in biomedical settings depend on accurate labels, yet annotating biomedical time-series data remains challenging. Algorithmic sample selection may…
Computational modeling of early language learning from acoustic speech and audiovisual input without linguistic priors
Okko Räsänen
Learning to understand speech appears almost effortless for typically developing infants, yet from an information-processing perspective, acquiring a language from acoustic speech…
Investigating Affect Mining Techniques for Annotation Sample Selection in the Creation of Finnish Affective Speech Corpus
Kalle Lahtinen, Einari Vaaras, Liisa Mustanoja +1
Study of affect in speech requires suitable data, as emotional expression and perception vary across languages. Until now, no corpus has existed for natural expression of affect in…