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The presence of Lombard Effect in speech is proven to have severe effects on the performance of speech systems, especially speaker recognition. Varying kinds of Lombard speech are produced by speakers under influence of varying noise types  . This study proposes a high-accuracy classifier using deep neural networks for detecting various kinds of Lombard speech against neutral speech, independent of the noise levels causing the Lombard Effect. Lombard Effect detection accuracies as high asdoi:10.1109/icassp.2015.7178792 dblp:conf/icassp/SaleemLH15 fatcat:rrlosolt7fhvthzrcwhbcmbrfq