This report presents the work done over 22 weeks of internship within the Sound Perception and Design team of the Sciences and Technologies of Music and Sound (STMS) laboratory at the Institute for Research and Coordination in Acoustics/Music (IRCAM). As part of the launch of the project Reducing Noise with Augmented Reality (ReNAR); which aims to create a tool to reduce in real-time the cognitive impact of sounds perceived as unpleasant or annoying in indoor environments; an initial study was conducted to validate the feasibility and effectiveness of a new masking approach called concealer. The main hypothesis is that the concealer approach could provide better results than a masker approach in terms of perceived pleasantness. Mixtures of two noise sources (ventilation) and five masking sounds (water sounds) were generated using both approaches at various levels. The evaluation of the perceived pleasantness of these mixtures showed that the masker approach remains more effective than the concealer approach, regardless of the noise source, water sound, or level used.