Atwell, ES and McKevitt, P (1994) Pragmatic linguistic constraint models for large-vocabulary speech processing. In: Proceedings of the Twelfth National Conference on Artificial Intelligence. Integrating Speech and Natural Language Processing: AAAI94 Workshop, 31 July 1994, Seattle, Washington USA. AAAI Press , 58 - 64.
Abstract
Current systems for speech recognition suffer from uncertainty: rather than delivering a uniquely-identified word, each input segment is associated with a set of recognition candidates or word-hypotheses. Thus an input sequence of sounds or images leads to, not an unambiguous sequence of words, but a lattice of word-hypotheses. To choose the best candidate from each word-hypothesis set (i.e. to find the best route through the lattice) , linguistic context needs to be taken into account, at several levels: lexis and morphology, parts-of-speech, phrase structure, semantics and pragmatics. We believe that an intuitively simple, naive model will suffice at each level; the sophistication required for full Natural Language Understanding (NLU) (e.g. Alvey Natural Language Toolkit (ANLT)) is inappropriate for real-time language recognition. We describe here models of each linguistic level which are simple but robust and computationally straightforward (hence `pragmatic' in the everyday sense) and which have clear theoretical shortcomings in the eyes of linguistic purists but which nevertheless do the job.
Metadata
Item Type: | Proceedings Paper |
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Authors/Creators: |
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Copyright, Publisher and Additional Information: | Atwell, ES and McKevitt, P (c) 1994, University of Leeds. Reproduced with permission from the copyright holders. |
Dates: |
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Institution: | The University of Leeds |
Academic Units: | The University of Leeds > Faculty of Engineering & Physical Sciences (Leeds) > School of Computing (Leeds) > Artificial Intelligence & Biological Systems (Leeds) |
Depositing User: | Symplectic Publications |
Date Deposited: | 25 Nov 2014 12:27 |
Last Modified: | 01 Feb 2018 08:34 |
Published Version: | http://www.aaai.org/Library/AAAI/aaai94contents.ph... |
Status: | Published |
Publisher: | AAAI Press |
Open Archives Initiative ID (OAI ID): | oai:eprints.whiterose.ac.uk:81175 |