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Correlation of Fr\'echet Audio Distance With Human Perception of Environmental Audio Is Embedding Dependant

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arxiv 2403.17508 v1 pith:4KQ52OF3 submitted 2024-03-26 cs.SD eess.AS

Modan Tailleur , Junwon Lee , Mathieu Lagrange , Keunwoo Choi , Laurie M. Heller , Keisuke Imoto , Yuki Okamoto This is my paper
classification cs.SDeess.AS
keywords audiocorrelationechetembeddingembeddingsenvironmentalperceptualdistance
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This paper explores whether considering alternative domain-specific embeddings to calculate the Fr\'echet Audio Distance (FAD) metric can help the FAD to correlate better with perceptual ratings of environmental sounds. We used embeddings from VGGish, PANNs, MS-CLAP, L-CLAP, and MERT, which are tailored for either music or environmental sound evaluation. The FAD scores were calculated for sounds from the DCASE 2023 Task 7 dataset. Using perceptual data from the same task, we find that PANNs-WGM-LogMel produces the best correlation between FAD scores and perceptual ratings of both audio quality and perceived fit with a Spearman correlation higher than 0.5. We also find that music-specific embeddings resulted in significantly lower results. Interestingly, VGGish, the embedding used for the original Fr\'echet calculation, yielded a correlation below 0.1. These results underscore the critical importance of the choice of embedding for the FAD metric design.

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Cited by 2 Pith papers

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