Speech-as-data technologies for personal information devices

 For small, portable devices, speech input has the advantages of low-cost and small hardware, can be used on the move or whilst the eyes & hands are busy, and is natural and quick. Rather than rely on imperfect speech recognition we propose that information entered as speech is kept as speech and suitable tools are provided to allow quick and easy access to the speech-as-data records. This paper summarises our work on the technologies needed for these tools – for organising, browsing, searching and compressing the stored speech. These technologies go a long way towards giving stored speech the characteristics of text without the associated input problems. Received: 5 March 2002 / Accepted: 1 September 2002 Nick Haddock Consultant Acknowledgements The authors would like to thank the whole HP Labs Gryphon team for their valuable contributions to this work - Mike Collins for the hierarchical chunking algorithm, Erik Geelhoed and David Frohlich for the users perspective, Richard Hull for starting off the compression work, Steve Loughran for productisation, and Dave Reynolds for his consistent advice and support. We would also like to thank our partners at Cambridge University, Steve Young and Tony Robinson, whose expertise and technology formed the foundation for this work, as well as the efforts of Kate Knill on wordspotting, Carl Seymour on compression, James Christie on recognition, and Robin Valenza whose brief excursion into the world of speech technology helped develop a simple and effective summarisation technique. Finally we would like to thank the reviewers for their many helpful comments.