Abstract
This work aims at modifying speech signal samples and test them with objective speech quality indicators after mixing the original signals with noise or with an interfering signal. Modifications that are applied to the signal are related to the Lombard speech characteristics, i.e., pitch shifting, utterance duration changes, vocal tract scaling, manipulation of formants. A set of words and sentences in Polish, recorded in silence, as well as in the presence of interfering signals, i.e., pink noise and the so-called babble speech, also referred to as the “cocktail-party” effect is utilized. Speech samples were then processed and measured utilizing objective indicators to check whether modifications applied to the signal in the presence of noise increased values of the speech quality index, i.e., PESQ (Perceptual Evaluation of Speech Quality) standard.
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Kąkol, K., Korvel, G., Kostek, B. (2020). Improving Objective Speech Quality Indicators in Noise Conditions. In: Dzemyda, G., Bernatavičienė, J., Kacprzyk, J. (eds) Data Science: New Issues, Challenges and Applications. Studies in Computational Intelligence, vol 869. Springer, Cham. https://doi.org/10.1007/978-3-030-39250-5_11
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