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superwhisper/s1-mini
Superwhisper's S1-mini is a 0.6B parameter model specialized in cleaning up messy speech-to-text transcripts.
What: S1-mini is a lightweight model designed to normalize raw automatic speech recognition (ASR) outputs into formatted text, achieving 94.8% token accuracy while running locally on CPU.
Why it matters: As ASR becomes ubiquitous, post-processing models that can run on low-resource hardware are essential for turning unformatted transcripts into usable documentation.
Decoder
- ASR (Automatic Speech Recognition): Technology that converts spoken language into text.
Original article
Superwhisper's S1-mini model is a 0.6B-parameter text normalizer for speech-to-text outputs, achieving a 94.8% token accuracy in transforming raw ASR transcripts into clean written text. It's optimized for English, runs comfortably on CPU, and requires a specific input format, including a control line for styling, structure, and context settings.
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