Vocabulary and language model adaptation using information retrieval

The goal of vocabulary optimization is to construct a vo- cabulary with exactly those words that are the most likely to appear in the test data. We will present a new ap- proach to reduce the out-of-vocabulary (OOV) rate by adapting the vocabulary model during the ASR process. This method can also be used for the statistical language model (SLM) adaptation. An information retrieval sys- tem is used after the first pass of the ASR system to ob- tain a set of relevant documents. These documents are then used to generate the new vocabulary and/or corpus. In this paper, we propose a new retrieving method well- adapted for this purpose. Experiments were carried out on French with a 28% OOV rate reduction. Experiments were also carried out on English for the SLM adapta- tion, with 7.9% perplexity reduction, and minor WER improvement.