AISHELL-5 releases 100+ hours of real in-car multi-channel multi-speaker Mandarin speech, 40 hours of noise, and a baseline showing mainstream ASR models still fail badly on this task.
AISHELL-5 is suitable for speech sep- aration, speech enhancement, noise reduction, and automatic speech recognition (ASR) tasks targeting in-car scenarios
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AISHELL-5: The First Open-Source In-Car Multi-Channel Multi-Speaker Speech Dataset for Automatic Speech Diarization and Recognition
AISHELL-5 releases 100+ hours of real in-car multi-channel multi-speaker Mandarin speech, 40 hours of noise, and a baseline showing mainstream ASR models still fail badly on this task.