EHR-LAB participated in the Working Group activities of eVoiceNet COST Action CA24128 and the International Vocal Biomarkers Conference (IVBC 2026) held in Luxembourg.
Representing EHR-LAB, Assoc. Prof. Dr. Veysel Alcan participated in the Working Group and scientific networking activities of COST Action CA24128 – European Network to Advance the Development and Implementation of Vocal Biomarkers (eVoiceNet) in Luxembourg. eVoiceNet is an international COST network dedicated to advancing the development and clinical translation of vocal biomarkers through multidisciplinary collaboration, standardisation, artificial intelligence and audio signal processing, open and responsible science, and privacy-aware approaches.
Alongside the eVoiceNet activities, participation extended to the International Vocal Biomarkers Conference (IVBC 2026), organised by eVoiceNet in Luxembourg on 29–30 June 2026. IVBC 2026 also marked the first Annual Meeting of eVoiceNet and brought together researchers, clinicians, AI specialists, speech and voice processing researchers, industry representatives, and other stakeholders. More than 130 researchers, clinicians, and industry experts from 35 countries participated in the Luxembourg events.
Representing EHR-LAB at the conference, PhD Candidate Bothayna Sekkine presented our work entitled “Explainable Machine Learning Framework for Vocal Biomarker Identification in Neurological and Systemic Diseases” during the Pitch Session. Through pitch, oral, and poster presentations, IVBC 2026 provided a multidisciplinary platform for discussing recent scientific and technological developments in vocal biomarkers, artificial intelligence, and digital health.
Participation in the eVoiceNet Working Group activities and IVBC 2026 provided a valuable opportunity to meet researchers and representatives from universities, research centres, healthcare organisations, and industry across many countries, exchange ideas on current approaches in voice analysis and vocal biomarkers, and discuss opportunities for future international collaboration. The diversity of the eVoiceNet community also highlighted the importance of integrating expertise from engineering, medicine, artificial intelligence, speech sciences, data governance, and healthcare to facilitate the translation of vocal biomarkers from research into clinical practice.
For EHR-LAB, these interactions are particularly valuable for advancing our research on voice and speech signal analysis, disease-related vocal biomarkers, and explainable machine learning, while providing a foundation for new collaborative projects and strengthening our international research network.
