2026-07-072026-07-07http://salesiana.dossiersoluciones.com/handle/123456789/30594This 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 (10.5% overall and 33.5% on target vocabulary).8 pages, 29 figures, presented at ACL99, College Park, MarylandComputation and LanguageI.2.7text