check-script.json

{
  "id": "CheckScript",
  "description": "Checks that a take speaks its script, line by line, and saves the answer as JSON for get_output_text. It runs 'check_script' on 'input_audio' (an audio file, or a video's muxed soundtrack) against 'lines', the expected lines in order: strings, or {text, shot} objects naming the shot a line belongs in. H3 markup in a line is stripped, and a markup word heard spoken is 'tag_spoken'; [] means no speech is expected. 'shots' is optional: by default the take's own recorded shots are used, from its run manifest or keep_output sidecar. Findings are line_mismatch, tag_spoken, line_clipped_at_end, speech_where_silent and speech_in_silent_shot, each a place to listen before re-rolling. The defaults come from a two-model measurement (#609, job af5de241ca83): whisper-large-v3-turbo scored correct lines 0.71 to 1.00 and wrong or missing ones 0.00, so 'similarity' 0.6 separates them. Write numbers as words, as turbo hears them.",
  "variables": {
    "input_audio": "asset:take.wav",
    "lines": null,
    "shots": null,
    "model_name": "openai/whisper-large-v3-turbo",
    "similarity": 0.6
  },
  "steps": [
    {
      "name": "check",
      "task": {
        "command": "check_script",
        "arguments": {
          "audio": "variable:input_audio",
          "lines": "variable:lines",
          "shots": "variable:shots",
          "model_name": "variable:model_name",
          "similarity": "variable:similarity"
        }
      },
      "result": {
        "content_type": "application/json",
        "subfolder": "final"
      }
    }
  ]
}