A 106-hour, four-channel Mandarin egocentric speech benchmark for smart glasses with paired speaker-attributed ASR and understanding tasks finds overlap and acoustic reasoning remain the hardest problems.
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The SLT 2026 SmartGlasses Challenge: Benchmarking Egocentric Multi-Talker Speech Recognition and Understanding with Audio-Language Models
A 106-hour, four-channel Mandarin egocentric speech benchmark for smart glasses with paired speaker-attributed ASR and understanding tasks finds overlap and acoustic reasoning remain the hardest problems.