Evaluation of Fréchet Audio Distance with Bass Sounds - Assmar, Adelmo; Assis, Flávio (Anais do Simpósio Brasileiro de Computação Musical; 2025: Anais do XIX Simpósio Brasileiro de Computação Musical, 2025)
Objective metrics are important to determine the effectiveness of automatic audio processing, such as in denoising and music source separation. The Fréchet Audio Distance (FAD) is an objective metric that can be used to compare two sets of audios based on their statistical properties. An advantage of FAD when compared to traditional metrics is that FAD does not depend on the existence of the original clean version of processed or noisy audios to be evaluated. However, the effectiveness of the use of FAD has been divergent in the literature, requiring thus further investigation. In this paper we study the impact on FAD scores when different reference sets and models are used, for the restricted case of bass sounds. We studied the sensitivity of FAD to audio effects and noises and used it to evaluate denoising processes. We compared the results with a qualified subjective evaluation, carried out by people with experience with professional recording. We show that reference sets must be designed very specifically, as apparently equivalent sets might provide different results. We additionally highlight the usefulness of understanding FAD scores relatively, instead of absolutely.