Papers › EMALG: An Enhanced Mandarin Lombard Grid Corpus with Meaningful Sentences
EMALG: An Enhanced Mandarin Lombard Grid Corpus with Meaningful Sentences
Baifeng Li, Qingmu Liu, Yuhong Yang, Hongyang Chen, Weiping Tu, Song Lin
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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, meaningful sentences are more effective in enhancing the Lombard effect. Additionally, we uncover that female exhibit a more pronounced Lombard effect than male when uttering meaningful sentences. Moreover, our results reaffirm the consistency in the Lombard effect comparison between English and Mandarin found in previous research.
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