The article discusses a new method for improving language modeling in the task of retelling stories, which usually requires a lot of specific training data. The researchers developed a unique approach using mixture models and limited text data to create more accurate language models. By combining different types of language models and classes, they were able to significantly reduce perplexity by up to 61.6% and word error rate by 20.7%.