Two decades of statistical language modeling: where do we go from here?
Abstract
Statistical language models estimate the distribution of various natural language phenomena for the purpose of speech recognition and other language technologies. Since the first significant model was proposed in 1980, many attempts have been made to improve the state of the art. We review them, point to a few promising directions, and argue for a Bayesian approach to integration of linguistic theories with data.
- Publication:
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IEEE Proceedings
- Pub Date:
- August 2000
- DOI:
- Bibcode:
- 2000IEEEP..88.1270R
- Keywords:
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- Natural languages;
- Speech recognition;
- Bayesian methods;
- Probability distribution;
- Information retrieval;
- Training data;
- Associate members;
- Paper technology;
- Routing;
- Optical character recognition software