Indoor localization is an actively researched field due to there not being a universal solution found yet. Applications of such systems include but are not limited to indoor wayfinding and automated tour guides. In previous years multiple solutions were proposed. This work looks into the performance of an indoor location sensing system in the presence of background music and tries to improve the accuracy in such a scenario. To achieve that a denoising autoencoder is proposed as a preprocessing step aiming to remove the noise from the fingerprints used for localization. In the end, it is shown that the use of such a technique introduces a tradeoff between an accuracy drop in quiet environments but an accuracy increase in environments with music.