FLEURS: FEW-Shot Learning Evaluation of Universal Representations of Speech
FLEURS: FEW-Shot Learning Evaluation of Universal Representations of Speech
We introduce FLEURS, the Few-shot Learning Evaluation of Universal Representations of Speech benchmark. FLEURS is an n-way parallel speech dataset in 102 languages built on top of the machine translation FLoRes-101 benchmark, with approximately 12 hours of speech supervision per language. FLEURS can be used for a variety of speech …