Investigation of the Lombard effect based on a machine learning approach - Korvel, Gražina; Treigys, Povilas; Kąkol, Krzysztof; Kostek, Bożena (Zielona Góra: Uniwersytet Zielonogórski)
The Lombard effect is an involuntary increase in the speaker`s pitch, intensity, and duration in the presence of noise. It makes it possible to communicate in noisy environments more effectively. This study aims to investigate an efficient method for detecting the Lombard effect in uttered speech. The influence of interfering noise, room type, and the gender of the person on the detection process is examined. First, acoustic parameters related to speech changes produced by the Lombard effect are extracted. Mid-term statistics are built upon the parameters and used for the self-similarity matrix construction.
Keywords: Lombard effect; speech detection; noise signal; self-similarity matrix; convolutional neural network (CNN)