20 citations · 30 across the 3 of their papers we have counts for
6 papers
Language-Independent Approach for Automatic Computation of Vowel Articulation Features in Dysarthric Speech Assessment
Yuanyuan Liu, Nelly Penttilä, Tiina Ihalainen +3
Imprecise vowel articulation can be observed in people with Parkinson's disease (PD). Acoustic features measuring vowel articulation have been demonstrated to be effective indicato…
Comparison of end-to-end neural network architectures and data augmentation methods for automatic infant motility assessment using wearable sensors
Manu Airaksinen, Sampsa Vanhatalo, Okko Räsänen
Infant motility assessment using intelligent wearables is a promising new approach for assessment of infant neurophysiological development, and where efficient signal analysis play…
Unsupervised Discovery of Recurring Speech Patterns Using Probabilistic Adaptive Metrics
Okko Räsänen, María Andrea Cruz Blandón
Unsupervised spoken term discovery (UTD) aims at finding recurring segments of speech from a corpus of acoustic speech data. One potential approach to this problem is to use dynami…
Analysis of Predictive Coding Models for Phonemic Representation Learning in Small Datasets
María Andrea Cruz Blandón, Okko Räsänen
Neural network models using predictive coding are interesting from the viewpoint of computational modelling of human language acquisition, where the objective is to understand how…
A computational model of early language acquisition from audiovisual experiences of young infants
Okko Räsänen, Khazar Khorrami
Earlier research has suggested that human infants might use statistical dependencies between speech and non-linguistic multimodal input to bootstrap their language learning before…
SylNet: An Adaptable End-to-End Syllable Count Estimator for Speech
Shreyas Seshadri, Okko Räsänen
Automatic syllable count estimation (SCE) is used in a variety of applications ranging from speaking rate estimation to detecting social activity from wearable microphones or devel…