Wav2Vec2

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   Humans Edge Speech Models on Cocktail-Party Audio Benchmark

   A project by cloud_kj tested whether identifying one target voice amid background speech could distinguish humans from speech models. Across 40 synthetic clips and 146 human transcriptions from 18 sessions, humans averaged 0.71 word accuracy, compared with 0.54 for instructed Gemini 3.8 Flash and 0.55 for Qwen3-ASR 0.6B; the corresponding pass rates were 77% and 55%. The author concluded that the human-model gap was too narrow for the setup to work reliably as an audio CAPTCHA.

   r/MachineLearning · 🔥 0

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