Sound evaluation based on listening experiments is very costly and time-consuming. Alternatively, the sounds under evaluation can be compared using psychoacoustic metrics, under the hypothesis that sounds that differ by more than one just-noticeable difference (JND) are perceived as significantly different from each other. Wellestablished psychoacoustic metrics are obtained from models of loudness, sharpness, roughness, fluctuation strength, and tonality. In the present study, we use these psychoacoustic models to analyse a selection of aircraft flyovers and train pass-by sounds, as well as fluctuating sounds obtained from resonances of a rotating flexible tube. In addition to the description of the adopted model implementation of each psychoacoustic metric, our discussion focuses on technical and practical aspects including (1) the dependency of the results on the appropriate sound and model calibration, and (2) how to interpret the results based on reported JNDs from the literature. We reflect on how much we can rely on a specific model implementation considering the status of the metric—standardised (or not), accessibility to algorithms and to their validation results (or not)—and external factors that may influence the obtained estimates. @en

Literature suggests that psychoacoustic metrics, which are established by models firmly based on the human auditory system, are able to better approximate perceptual attributes of sounds in a quantitative manner than conventional metrics based on the sound pressure level. Therefore, psychoacoustic metrics are commonly used as sound quality indicators in practical applications, such as product design or environmental noise assessment, in which human perception plays an important role. However, their calculation is not straightforward and the non-availability of verified, well-documented, open-source implementations in a single environment poses a challenge to reproducible research. In this contribution, we introduce the sound quality analysis toolbox (SQAT), an open-source compilation of MATLAB codes containing the implementation of the following key psychoacoustic metrics: loudness (ISO 532-1:2017), sharpness (DIN 45692:2009), roughness (Daniel & Weber’s model), fluctuation strength (Osses et al. model), and tonality (Aures’ model). A comprehensive description of their implementation is provided. Furthermore, a verification study is presented in order to demonstrate the reliability of the implementations, supporting the use of SQAT as a reliable tool for future works in the field of sound quality assessment based on psychoacoustic metrics. @en