International audienceWhereas topic-based adaptation of language models (LM) claims to increase the accuracy of topic-specific words within automatic speech recognition, this paper investigates why this wish is not always verified. After outlining the mechanisms of LM adaptation and automatic speech recognition, diagnosing elements are proposed along with solutions. In addition to a better accuracy on topic-specific words, results show better graph error rates and word error rates on a set of spoken documents with various topic
