The evolution of voice technology, audio signal analysis and natural language processing/understanding methods have opened the way to numerous applications of voice tracking and analysis in the field of healthcare. Voice is a rich medium, in which a lot of information can be found, providing that we know how to isolate and make use of it. A vocal biomarker can be defined as a signature, a feature, or a combination of features from the audio signal of the voice that is associated with a clinical outcome and can be used to monitor patients, diagnose a condition or grade the severity or the stages of a disease or for drug development. People with diabetes frequently experienced diabetes distress. We want to test whether these events impact voice characteristics and whether we can predict these events based on voice features.
Our team aims at identifying vocal biomarkers of diabetes distress and fatigue based on audio recordings from the large Colive Voice study. This internship is part of the Vocadiab project, funded by the French Speaking Diabetes Society (SFD).
Training and research environment
The “Deep Digital Phenotyping Research Unit” develops a research activity within the Department of Population Health at the frontier between digital epidemiology, digital health and data science, to leverage real-world data to improve population health.
The Master student will directly contribute to the identification of vocal biomarkers for diabetes distress. He/she will lead a project on the analysis of an annotated audio dataset from the Colive Voice study to decompose the audio signals and then apply AI-based algorithms and statistical approaches to identify features associated with diabetes distress. He/She will have to take charge of the literature review, the pre-processing of the data, the data analysis, and the preparation of a scientific article. He/she will be supervised by Dr. G. Fagherazzi, Director of the Department of Precision Health and Abir Elbéji, PhD student in the DDP lab, in association with experts in audio signals and artificial intelligence methods.
This internship position may lead to a PhD opportunity in digital epidemiology.
- Master level in Data Science, Bioinformatics, Biostatistics or equivalent required.
- Flexibility, adaptability, autonomy
- Ability to work with different profiles and people from different experiences and cultural backgrounds
- Language skills: Fluency in French and English is an asset, with written skills in English. Any other language in use in Luxembourg would also be an asset.
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