In this paper, we present an efficient query selection algorithm for the retrieval of web text data to augment a statistical language model (LM). The number of retrieved relevant documents is optimized with respect to the number of queries submitted. The querying scheme is applied in the domain of SMS text messages. Continuous speech recognition experiments are conducted on three languages: English, Spanish, and French. The web data is utilized for augmenting in-domain LMs in general and for adapting the LMs to a user-specific vocabulary. .
