1. A computer-implemented method for building an n-gram language model for an automatic speech recognition, comprising: reading training text data and additional text data for the n-gram language model from storage, wherein the additional text data comprises a plurality of sentences having at least one target keyword; and building the n-gram language model by a smoothing algorithm having discount parameters for n-gram counts, wherein each discount parameter for each target keyword is tuned using development data which are different from the additional text data so that a predetermined balance between precision and recall is achieved.