Department of Engineering / Profiles / Prof. Phil Woodland

Department of Engineering

Prof. Phil Woodland


Phil Woodland


Academic Division: Information Engineering

Research group: Machine Intelligence

Telephone: +44 1223 3 32669


Personal website


Research interests

Prof. Woodland’s research is in the area on speech and language technology with a major focus on developing all aspects of large vocabulary speech recognition systems.

His group has developed a number of widely used techniques in current large vocabulary systems including standard methods for transform-based adaptation and discriminative training. He continues to have interests in these areas.  A current major interest is developing flexible systems that can adapt to a wide range of speakers, acoustic conditions, speaking style, etc., with relatively limited training resources. This includes work on unsupervised and lightly supervised training, Current work also includes techniques for improved language modelling and confidence estimation. An increasing trend in his work is the use of deep neural networks for both acoustic models and language models.

He is well known for his work on the HTK large vocabulary speech recognition systems.

He has also worked on audio indexing technology and is currently involved in work on keyword spotting techniques. He has also worked on auditory modelling and speech synthesis.

Research projects

  • Natural Speech Technology . Development of improved speech recognition and speech synthesis systems. ESPRC-funded programme with the Universities of Edinburgh and Sheffield (2011-2016)
  • BABEL: Speech recognition and keyword spotting in multiple languages. Funded by IARPA– subcontract to IBM (2012-2015)
  • Broad Operational Language Translation. Speech recognition and machine translation. Funded by DARPA– subcontract to IBM (2011-2016)
  • RATS. Recognition/keyword spotting for audio in degraded conditions. Funded by DARPA (subcontract to BBN) (2011-2014)
  • HTK Version 3. HMM toolkit. See
  • AGILE: Speech Recognition and Statistical Machine Translation from Arabic and Chinese. Funded by DARPA (subcontract to BBN) (2005-2011)
  • HTK Rich Audio Transcription. Speech recognition and metadata generation for broadcast and conversational data. Funded by  – DARPA (2002-2005)

Teaching activity

  • MPhil in Advanced Computer Science: Spoken Language Processing (L106)
  • 4th year engineering undergraduates: Speech and Language Processing (4F11)
  • 1st year engineering undergraduates: Mathematics (Michaelmas Term, fast course)

Other positions

  • Professorial Fellow of Peterhouse
  • Steering Committee for Cambridge Language Sciences Initiative