Mikko Kurimo

CASA not only sets a new benchmark in automatic speaking assessment but also clarifies how acoustic and content features interact, paving the way for more interpretable AI assessments.

Achieving an 8x reduction in training time without sacrificing ASR performance could revolutionize how we deploy speech recognition systems for dysarthric users.

Tailored acoustic feature selection can boost dysarthric speech recognition accuracy by over 4.6%, transforming how we approach ASR for low-resource groups.

Tailored acoustic features can boost dysarthric speech recognition performance by over 4% using advanced neural network models.