EMALG: An Enhanced Mandarin Lombard Grid Corpus with Meaningful Sentences

TL;DR

This paper introduces EMALG, an improved Mandarin Lombard grid corpus with meaningful sentences, demonstrating its effectiveness in studying the Lombard effect and revealing gender differences in speech adaptation.

Contribution

The study presents EMALG, a new Mandarin Lombard corpus with meaningful sentences and enhanced recording conditions, addressing limitations of previous nonsense sentence datasets.

Findings

Meaningful sentences better evoke the Lombard effect in Mandarin.

Females show a more pronounced Lombard effect than males.

Results align with previous English-Mandarin Lombard effect comparisons.

Abstract

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.