113 citations · 275 across the 15 of their papers we have counts for
6 papers · 1 filter
Wav2vec-based Detection and Severity Level Classification of Dysarthria from Speech
Farhad Javanmardi, Saska Tirronen, Manila Kodali +2
Automatic detection and severity level classification of dysarthria directly from acoustic speech signals can be used as a tool in medical diagnosis. In this work, the pre-trained…
Analysis and Detection of Pathological Voice using Glottal Source Features
Sudarsana Reddy Kadiri, Paavo Alku
Automatic detection of voice pathology enables objective assessment and earlier intervention for the diagnosis. This study provides a systematic analysis of glottal source features…
Time-Varying Quasi-Closed-Phase Analysis for Accurate Formant Tracking in Speech Signals
Dhananjaya Gowda, Sudarsana Reddy Kadiri, Brad Story +1
In this paper, we propose a new method for the accurate estimation and tracking of formants in speech signals using time-varying quasi-closed-phase (TVQCP) analysis. Conventional f…
Refining a Deep Learning-based Formant Tracker using Linear Prediction Methods
Paavo Alku, Sudarsana Reddy Kadiri, Dhananjaya Gowda
In this study, formant tracking is investigated by refining the formants tracked by an existing data-driven tracker, DeepFormants, using the formants estimated in a model-driven ma…
Severity Classification of Parkinson's Disease from Speech using Single Frequency Filtering-based Features
Sudarsana Reddy Kadiri, Manila Kodali, Paavo Alku
Developing objective methods for assessing the severity of Parkinson's disease (PD) is crucial for improving the diagnosis and treatment. This study proposes two sets of novel feat…
Investigation of Self-supervised Pre-trained Models for Classification of Voice Quality from Speech and Neck Surface Accelerometer Signals
Sudarsana Reddy Kadiri, Farhad Javanmardi, Paavo Alku
Prior studies in the automatic classification of voice quality have mainly studied the use of the acoustic speech signal as input. Recently, a few studies have been carried out by…