Tron Vedul Tronstad

Tron Vedul Tronstad is an Associate Professor at the Department of Electronic Systems, Faculty of Information Technology and Electrical Engineering, Norwegian University of Science and Technology (NTNU), and a Researcher at Sustainable Communication Technologies, SINTEF AS. His interdisciplinary work bridges engineering and clinical applications in hearing and communication technologies.

His research interests focus on acoustic signal processing, speech communication, hearing assessment tools, and classroom acoustics, particularly in low-resource settings. He has led projects adapting standardized hearing tests like the Digit Triplet Test for Swahili speakers and evaluating real-world acoustic conditions in Tanzanian classrooms. His work emphasizes global hearing health and accessible auditory diagnostics.

The recent publications reflect a strong trend in speech intelligibility under noise and reverberation, cross-linguistic validation of hearing tests, and measurement of listening effort in assistive technologies. These efforts span disciplines including audiology, acoustical engineering, and public health.

Scientific Contributions:

• Development of culturally and linguistically adapted hearing assessments
• Field studies on educational acoustics in sub-Saharan Africa
• Innovative evaluation methods for speech enhancement systems

Tronstad actively collaborates with institutions such as SINTEF, NTNU, University of Oslo (UIO), and the University of Girona (UdG). He contributes to advancing sustainable communication technologies through research, development, and international dissemination. While no formal students or grants are listed in the provided text, his project-based work suggests involvement in funded research initiatives and supervision within SINTEF-NTNU collaborative frameworks.

He is affiliated with research environments focused on auditory technology innovation and sustainable communication solutions, particularly through the SINTEF-NTNU partnership in electronic systems and health-related signal processing.