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JevMade field notes / Architecture walkthrough

Build a bounded reading-assessment pipeline with Jev

DaSheng documents an end-to-end reading practice pipeline in which streaming transcription supplies timestamped text, Jev makes bounded textual judgments, and local code computes highlights and scores.

Original by wquguruEvaluationGitHub READMESource reviewed

Before you dive in

What you’ll find in the original

  1. Keep streaming transcription append-only and timestamped before aligning it with the expected passage.
  2. Use noul for word equivalence, choice for error categories, and score for whether speech still belongs to the same sentence.
  3. Compute totals locally and do not claim pronunciation, stress, or accent scores from a text-only judge.
Worth knowing

Requires the project's transcription and Jev services. The workflow evaluates textual alignment, not acoustic pronunciation quality, and its README does not establish benchmark accuracy.

More guides →See the experiments →