Stephen Renals

Professor of Speech Technology at University of Edinburgh

Biography

Steve Renals is professor of Speech Technology in the School of Informatics, at the University of Edinburgh. He received a BSc in Chemistry from the University of Sheffield in 1986, an MSc in Artificial Intelligence from the University of Edinburgh in 1987, and a PhD in Speech Recognition and Neural Networks, also from Edinburgh, in 1990. From 1991-92 he was a postdoctoral fellow at the International Computer Science Institute (ICSI), Berkeley, and was then an EPSRC postdoctoral fellow in Information Engineering at the University of Cambridge (1992-94). From 1994-2003 he was lecturer, then reader, in Computer Science at the University of Sheffield, moving to Edinburgh in 2003.

He has over 250 publications in speech and language processing, and has led several large projects in the field, including the EU project SUMMA, the EPSRC Programme Grant Natural Speech Technology and the AMI and AMIDA Integrated Projects. He is a fellow of the IEEE, and a fellow of ISCA.

Qualifications

  • 1991 Doctor of Philosophy, PhD, University of Edinburgh
    Speech recognition and neural network dynamics
  • 1987 Master of Science, University of Edinburgh
    A connectionist approach to speech recognition
  • 1986 Bachelor of Science, 1st, University of Sheffield

Research Interests

My research is about the development of interactive systems that can understand human communication. A lot of this work is grounded in speech recognition, and is based on building and applying statistical models to interpret communication signals. The Natural Speech Technology programme grant is concerned with core work in speech recognition and speech synthesis.

Speech to text transcription is a highly challenging task in itself, but ultimately we want to understand human communication, rather than only transcribing the words. Along these lines, we have done work concerned with interpreting and accessing information from speech, and multimodal interaction. For more than a decade now, a lot of our work has focussed on the recognition and interpretation of multiparty meetings, as part of the M4, AMI, AMIDA, and InEvent projects.

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