Sixth European Conference on Speech Communication and Technology
A new language model for speech recognition inspired by lin-guistic analysis is presented. The model develops hidden hierar-chical 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 trigrammodels. The structured lan-guage model, its probabilistic parameterization and performance in a two-pass speech recognizer are presented. Experiments on the SWITCHBOARD corpus show an improvement in both per-plexity and word error rate over conventional trigram models.
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Bibliographic reference. Chelba, Ciprian / Jelinek, Frederick (1999): "Recognition performance of a structured language model", In EUROSPEECH'99, 1567-1570.