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This study explores how sentence types affect the Lombard effect andintelligibility enhancement, focusing on comparisons between natural and gridsentences. Using the Lombard Chinese-TIMIT (LCT) corpus and the EnhancedMAndarin Lombard Grid (EMALG) corpus, we analyze changes in phonetic andacoustic features across different noise levels. Our results show that gridsentences produce more pronounced Lombard effects than natural sentences. Then,we develop and test a normal-to-Lombard conversion model, trained separately onLCT and EMALG corpora. Through subjective and objective evaluations, naturalsentences are superior in maintaining speech quality in intelligibilityenhancement. In contrast, grid sentences could provide superior intelligibilitydue to the more pronounced Lombard effect. This study provides a valuableperspective on enhancing speech communication in noisy environments.

Exploring Sentence Type Effects on the Lombard Effect and Intelligibility Enhancement: A Comparative Study of Natural and Grid Sentences