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Professor Andrew Lambourne

About Professor Andrew Lambourne

Andrew Lambourne's career has focused on the design and development of computer-assistive tools which help busy professionals to become more productive, particularly in the areas of speech and language technology and textual information processing.

Andrew's R&D credentials were forged in the broadcast technology market where he pioneered many of the tools and techniques which make it possible to provide live TV subtitles for deaf and hearing-impaired people, as well as cost-effective subtitles for recorded programmes. He also created market-leading systems for the production and delivery of information services - starting with broadcast teletext and leading to the digital text and interactive services ancillary to TV broadcasts.

He has extensive experience with using speech recognition and various transcription systems since 1995, and managed the development of a patented real-time speech-to-text alignment and speech following technology. Since live subtitling aims to achieve perfection in real-time transcription, Andrew has investigated and refined the techniques which can be used to maximise quality and accuracy, and has trained live re-speakers around the UK and Europe.

With an interest in workflow support tools in general, he advises on how to set up productive partnerships between people and technology so as to get the best from the skills and capabilities which each provide.

Research Interests

A specific focus of interest is looking at the gap between what the best speech and language tools for transcription, translation and alignment can currently achieve, and the corresponding capability of a human being. This clearly illuminates areas which touch on true AI, such as how the rich cognitive processing performed by the human brain can better be modelled in a computer environment, in order to move from purely statistical processing to more semantically informed techniques.

Research in these areas will benefit not only the huge demand for fast, accurate transcription of meetings, media content and live TV broadcasts, but also touches on the challenges of making translation engines more accurate and capable. At the same time it continues to deliver insights into what truly constitutes intelligence, and how the brain does such a fantastic job of making sense from noisy, faulty input.

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