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:

Source: Hugging Face Hub (espnet/floras). Metadata imported from the dataset’s Hub tags.