Matt Coler ☕️
Matt Coler

Associate Professor of Speech Technology

About Me

I am head of the Technology, Governance and Innovation department and Associate Professor of Speech Technology, at Campus Fryslân, University of Groningen, where I also direct the MSc Speech Technology program. I earned my PhD from the Free University of Amsterdam in 2010 and previously led cognitive systems at an AI startup specializing in acoustic sensors. I served as Vice Chair of the LITHME COST Action and currently serve on the ISCA Ethics Committee and the ISCA SynSIG Board.

View CV
Interests
  • Speech Technology
  • Language Diversity
  • Auditory perception
  • Ethics in AI
Education
  • PhD Linguistics

    Free University Amsterdam

  • MA Linguistics (cum laude)

    Free University Amsterdam

  • Graduate Studies

    New York University

  • BA Philosophy & Chinese

    University of Massachusetts

📚 My Research

My research centers on the ethical development of speech technology, with particular focus on under-resourced languages and small data scenarios. As Ethics Chair for INTERSPEECH 2025 and member of the ISCA Ethics Committee and ISCA SynSIG Board, I advocate for responsible AI development that prioritizes linguistic diversity and community benefit over technological advancement alone.

I explore how speech technologies can be developed ethically to serve marginalized language communities, ensuring that AI systems amplify linguistic diversity. I welcome collaboration opportunities at the intersection of AI ethics, speech technology, and social justice. 🔊

Featured Publications
Recent Publications
(2025). Intra-modal Relation and Emotional Incongruity Learning using Graph Attention Networks for Multimodal Sarcasm Detection. In ICASSP 2025.
(2025). Enhancing Standard and Dialectal Frisian ASR: Multilingual Fine-tuning and Language Identification for Improved Low-resource Performance. ICASSP 2025.
(2025). Evaluating Standard and Dialectal Frisian ASR: Multilingual Fine-tuning and Language Identification for Improved Low-resource Performance. arXiv.
(2024). AMuSeD: An Attentive Deep Neural Network for Multimodal Sarcasm Detection Incorporating Bi-modal Data Augmentation. arXiv.
(2024). Lexical Stress Identification in Cochlear Implant-Simulated Speech by Non-Native Listeners. Lang. Speech.
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