A Structured Language Model

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 n-gram Markov models. The model, its probabilistic parametrization, a reestimation algorithm for the model parameters and a set of experiments meant to evaluate its potential for speech recognition are presented.

• Type: Conference
• Year: 1997
• Where: ACL
• Authors: Ciprian Chelba
• Keywords: ACL 1997, ACL 2007, Model Parameters, N-gram Markov Models, Speech Recognition