Experiments with Linguistic Categories for Language Model Optimization

In this work1 we obtain robust category-based language models to be integrated into speech recognition systems. Deductive rules are used to select linguistic categories and to match words with categories. Statistical techniques are then used to build n-gram Language Models based on lexicons that consist of sets of categories. The categorization procedure and the language model evaluation were carried out on a taskoriented Spanish corpus. The cooperation between deductive and inductive approaches has proved efficient in building small, reliable language models for speech understanding purposes.

• Type: Conference
• Year: 2003
• Where: CICLING
• Authors: Arantza Casillas, Amparo Varona, Inés Torres
• Keywords: Category-based Language Models, CICLING 2003, Language Models, N-gram Language Models, Natural Language Processing