at r = 1% both sampling methods result in similar FAD score while the two subsets exhibit very
different levels of diversity. We hypothesize that this is because FAD score is computed based on
features extracted from an audio even classifier trained on AudioSet, which learns to distinguish
between events like lawn mower, car engine, and human speech, but does not learn to capture the
variation within speech, such as different voices.
Voicebox-Text-GuidedMultilingual UniversalSpeechGenerationatScale