This study investigates the Lombard effect, where individuals adapt their speech in noisy environments. We introduce an enhanced Mandarin Lombard grid (EMALG) corpus with meaningful sentences , enhancing the Mandarin Lombard grid (MALG) corpus. EMALG features 34 speakers and improves recording setups, addressing challenges faced by MALG with nonsense sentences. Our findings reveal that in Mandarin, female exhibit a more pronounced Lombard effect than male, particularly when uttering meaningful sentences. Additionally, we uncover that nonsense sentences negatively impact Lombard effect analysis. Moreover, our results reaffirm the consistency in the Lombard effect comparison between English and Mandarin found in previous research.

翻译：本研究探讨了隆巴德效应，即个体在嘈杂环境中调整其语音的现象。我们引入了一种带有有意义句子的增强型普通话隆巴德网格（EMALG）语料库，对普通话隆巴德网格（MALG）语料库进行了改进。EMALG包含34位说话人，并改进了录音设置，解决了MALG使用无意义句子所面临的挑战。我们的研究结果发现，在普通话中，女性比男性表现出更显著的隆巴德效应，尤其是在发出有意义的句子时。此外，我们揭示了无意义句子对隆巴德效应分析产生负面影响。同时，我们的结果再次证实了先前研究中发现的英语与普通话之间隆巴德效应比较的一致性。