espnet/floras

FLORAS FLORAS is a 50-language benchmark For LOng-form Recognition And Summarization of spoken language. The goal of FLORAS is to create a more realistic benchmarking environment for speech recognition, translation, and summarization models. Unlike typical academic benchmarks like LibriSpeech and FLEURS that uses pre-segmented single-speaker read-speech, FLORAS tests the capabilities of models on raw long-form conversational audio, which can have one or many speakers. To… See the full description on the dataset page: https://huggingface.co/datasets/espnet/floras.

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