Automated Cross-language Intelligibility Analysis of Parkinson's Disease Patients Using Speech Recognition Technologies
| Autor: | Nina Hosseini-Kivanani, Elmar Nöth, Juan Camilo Vásquez-Correa, Manfred Stede |
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| Předmět: |
Czech
Parkinson's disease Computer science Speech recognition 020206 networking & telecommunications 02 engineering and technology Intelligibility (communication) medicine.disease language.human_language German 030507 speech-language pathology & audiology 03 medical and health sciences 0202 electrical engineering electronic engineering information engineering language medicine Phonation 0305 other medical science Prosody |
| Zdroj: | Publons ACL (2) |
| Popis: | Speech deficits are common symptoms amongParkinson’s Disease (PD) patients. The automatic assessment of speech signals is promising for the evaluation of the neurological state and the speech quality of the patients. Recently, progress has been made in applying machine learning and computational methods to automatically evaluate the speech of PD patients. In the present study, we plan to analyze the speech signals of PD patients and healthy control (HC) subjects in three different languages: German, Spanish, and Czech, with the aim to identify biomarkers to discriminate between PD patients and HC subjects and to evaluate the neurological state of the patients. Therefore, the main contribution of this study is the automatic classification of PD patients and HC subjects in different languages with focusing on phonation, articulation, and prosody. We will focus on an intelligibility analysis based on automatic speech recognition systems trained on these three languages. This is one of the first studies done that considers the evaluation of the speech of PD patients in different languages. The purpose of this research proposal is to build a model that can discriminate PD and HC subjects even when the language used for train and test is different. |
| Databáze: | OpenAIRE |
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