103 citations · 150 across the 5 of their papers we have counts for
4 papers · 1 filter
Dysfluencies Seldom Come Alone -- Detection as a Multi-Label Problem
Sebastian P. Bayerl, Dominik Wagner, Florian Hönig +3
Specially adapted speech recognition models are necessary to handle stuttered speech. For these to be used in a targeted manner, stuttered speech must be reliably detected. Recent…
Representation Learning Strategies to Model Pathological Speech: Effect of Multiple Spectral Resolutions
Gabriel Figueiredo Miller, Juan Camilo Vásquez-Correa, Juan Rafael Orozco-Arroyave +1
This paper considers a representation learning strategy to model speech signals from patients with Parkinson's disease and cleft lip and palate. In particular, it compares differen…
Common Phone: A Multilingual Dataset for Robust Acoustic Modelling
Philipp Klumpp, Tomás Arias-Vergara, Paula Andrea Pérez-Toro +2
Current state of the art acoustic models can easily comprise more than 100 million parameters. This growing complexity demands larger training datasets to maintain a decent general…
Comparison of user models based on GMM-UBM and i-vectors for speech, handwriting, and gait assessment of Parkinson's disease patients
J. C. Vasquez-Correa, T. Bocklet, J. R. Orozco-Arroyave +1
Parkinson's disease is a neurodegenerative disorder characterized by the presence of different motor impairments. Information from speech, handwriting, and gait signals have been c…