This paper presents a novel method of generating and applying hierarchical, dynamic topic-based language models. It proposes and evaluates new cluster generation, hierarchical smoothing and adaptive topic-probability estimation techniques. These combined models help capture long-distance lexical dependencies. °Experiments on the Broadcast News corpus show significant improvement in perplexity ( overall and on target vocabulary).