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Add human‑level pronunciation assessment to your app with a single API call. Built for EdTech, speech therapy, and linguistic analysis.

Getting started

Make your first API request in minutes.

Output reference

Learn the JSON schema and fields.

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API overview

Langcraft Speech API provides pronunciation assessment and prosody analysis in a single call. It’s designed for EdTech, speech therapy, and linguistic analysis, and returns structured JSON you can use directly in your app. Key capabilities:
  • Word and phoneme alignment with millisecond timing
  • Phoneme‑level scoring and error detection
  • Automatic transcription with word‑level timestamps when no reference text is provided
  • Multilingual support (40+ languages)
  • Model selection: send model=aurora-1 for languages other than English, or leave model unset for standard English analysis

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Highlights

  • Per‑phoneme scores with timestamps
  • Per‑word rollups and summaries
  • Pitch and stress contours at the phoneme and word levels
  • Alignment metadata to connect audio, phones, and text

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Inputs

You can analyze speech with any of:
  • A reference text (reference_text) plus language code (lang) — the API runs grapheme‑to‑phoneme generation to derive canonical phones
  • A direct IPA phone sequence (reference_phones) — bypasses G2P, useful for pronunciation contrast tests
  • Audio only — the API runs automatic transcription and uses the transcript as the reference
reference_text accepts the alias text. reference_phones accepts the alias ipa.

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Model selection

For non-English speech, set the official public model selector: 
model=aurora-1
aurora-1 is an experimental public model selector designed for languages other than English. It is currently recommended for German, French, and Spanish, and is the only non-default model selector currently documented for public integrations.