Skip to content

Syllable-calibrated runtime estimator #181

Description

@stultus

What

Replace the current page-equals-minute runtime heuristic with a syllable-calibrated estimator that uses per-language speech rates.

Why this matters

The page-equals-minute rule is an Anglo-Hollywood convention (one Courier-formatted page of English screenplay ≈ 60 seconds of screen time). It systematically under- or over-estimates Malayalam runtimes because Malayalam syllable density per visual line is different from English.

A syllable-calibrated estimator gives a far more accurate prediction:

  • Count syllables per dialogue line via mlphon.
  • Apply per-language base rate (Malayalam ≈ 5.5–6.5 syl/sec for normal delivery; English ≈ 4–5 syl/sec).
  • Sum syllables across dialogue, divide by rate → dialogue runtime.
  • Add action-line runtime via existing page-eighths math (action is paced page-equals-minute reasonably).
  • Total = dialogue runtime + action runtime.

Output: "117 minutes — 49 min dialogue at 5.8 syl/sec, 68 min action at standard pacing."

Why not Tier 2 #5 (naturality scoring)

Skipped per the planning discussion — the Malayalam Speech Corpus isn't dense enough yet to derive per-genre rates with confidence. This issue uses a literature-derived constant (5.8 syl/sec for spoken Malayalam, citation needed in the doc) as the v1 default. Per-character calibration via the Statistics tab can come later if the corpus grows.

Dependency

mlphon's syllable counter. Or, simpler v1: a self-contained Rust syllabifier following Malayalam syllable rules (consonant + dependent vowel = one syllable; consonant cluster + vowel = one syllable; etc. — a few hundred lines).

Technical sketch

  • Add a syllableCount(text: string) Rust helper.
  • Walk dialogue blocks in computeStats, sum syllables.
  • Configurable rate constant via Settings → Writing.
  • Surface in the Overview tab as the new "Estimated screen time" replacing pageCount-as-minute.

Out of scope

Per-character speech rate tuning, dialect adjustments, accent modeling — all are Tier 2 follow-ups.

Activity

Sign up for free to join this conversation on GitHub. Already have an account? Sign in to comment

Metadata

Metadata

Assignees

No one assigned

    Labels

    enhancementNew feature or request

    Projects

    No projects

      Milestone

      No milestone

      Relationships

      None yet

      Development

      No branches or pull requests

      Issue actions