no code implementations • 13 Jul 2019 • Pavol Harar, Zoltan Galaz, Jesus B. Alonso-Hernandez, Jiri Mekyska, Radim Burget, Zdenek Smekal
Automatic objective non-invasive detection of pathological voice based on computerized analysis of acoustic signals can play an important role in early diagnosis, progression tracking and even effective treatment of pathological voices.
no code implementations • 12 Jul 2019 • Pavol Harar, Jesus B. Alonso-Hernandez, Jiri Mekyska, Zoltan Galaz, Radim Burget, Zdenek Smekal
This paper describes a preliminary investigation of Voice Pathology Detection using Deep Neural Networks (DNN).
no code implementations • 18 Mar 2022 • Jan Mucha, Zoltan Galaz, Jiri Mekyska, Tomas Kiska, Vojtech Zvoncak, Zdenek Smekal, Ilona Eliasova, Martina Mrackova, Milena Kostalova, Irena Rektorova, Marcos Faundez-Zanuy, Jesus B. Alonso-Hernandez
In this work, we analysed the power of conventional speech features quantifying imprecise articulation, dysprosody, speech dysfluency and speech quality deterioration extracted from a specialized poem recitation task to discriminate dysarthric and healthy speech.