EmbeddingGemma 2 repurposed into on-device speech-to-text model
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A small reader trained on under two hours of 8xH100 turns Google's EmbeddingGemma 2 embedding model into an STT system that transcribes an hour of audio in ~13 seconds on a base M3 MacBook Air (288x real time). Word error rate is ~5% versus 2-3% for leading speech models; the 715 MB model runs on the Neural Engine with audio never leaving the machine.
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2 days · 0 reports · 3 community posts · from Oct 12
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