MAndarin Lombard

Mandarin Lombard speech research focuses on understanding how Mandarin speakers adjust their speech in noisy environments to maintain intelligibility, a phenomenon known as the Lombard effect. Current studies investigate the impact of different noise types and levels on speech characteristics, comparing the effectiveness of meaningful versus nonsense sentences in eliciting the Lombard effect and exploring the performance of machine learning models, such as StarGAN, in improving speech intelligibility in Lombard speech. These findings are crucial for developing more robust speech recognition and enhancement technologies, particularly in noisy conditions, and for a deeper understanding of human speech adaptation mechanisms.