Recognition Performance of a Structured Language Model

Details Recognition Performance of a Structured Language Model Recognition Performance of a Structured Language Model

2000-01-24

arxiv.org/abs/cs/0001022v1

Proceedings of Eurospeech, 1999, pp. 1567-1570, Budapest, Hungary

Computer Science

Computation and Language

4 pages

Scientific paper

A new language model for speech recognition inspired by linguistic analysis is presented. The model develops hidden hierarchical structure incrementally and uses it to extract meaningful information from the word history - thus enabling the use of extended distance dependencies - in an attempt to complement the locality of currently used trigram models. The structured language model, its probabilistic parameterization and performance in a two-pass speech recognizer are presented. Experiments on the SWITCHBOARD corpus show an improvement in both perplexity and word error rate over conventional trigram models.

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