Sabdakunjaशब्दकुञ्ज

Platform

Sabdakunja as a platform, not a single project.

Give us a language and a community, and the same three capabilities apply: make it AI-ready, collect and model its data, and preserve the culture carried inside it.

01

AI preparedness

Make a language machine-ready.

We audit what exists for a language, define orthography and transliteration standards, build annotation guidelines and evaluation benchmarks, so a community's language can enter modern speech and text systems without being distorted.

  • —Language readiness audit and gap map
  • —Orthography, romanization and tokenization standards
  • —ASR and translation benchmark sets
  • —Ethical consent, licensing and FAIR archival plan

02

Data collection & model development

Gold-quality voice and text at scale.

Native speakers record structured prompts and free speech; every hour is transcribed, aligned and validated. From those corpora we fine-tune ASR, TTS, translation and chat models that actually work in the language.

  • —Structured sentence corpora with native speaker recordings
  • —Parallel text corpora and human-verified transcription
  • —Speaker, dialect and quality metadata on every file
  • —Fine-tuning for ASR, TTS, MT and conversational agents

03

Cultural preservation

Keep the knowledge, not just the data.

Songs, proverbs, rituals, place names and elder testimony are recorded with context and returned to the community as learning material — archives that serve speakers first and models second.

  • —Cultural-linguistic repositories of oral tradition
  • —Community-owned archives and bilingual learning material
  • —ShabdPatra flashcards, phrasebooks and script guides
  • —Youth and school revitalisation programmes

How an engagement runs

  1. Step 1

    Engage

    Community agreement, consent framework and speaker recruitment.

  2. Step 2

    Prepare

    Orthography decisions, prompt scripts, annotation guidelines.

  3. Step 3

    Record

    Structured sentences plus free and cultural speech, in studio or field.

  4. Step 4

    Validate

    Transcription, alignment, dual review, dialect and quality tagging.

  5. Step 5

    Train

    Fine-tuning ASR, TTS, translation and conversational models.

  6. Step 6

    Return

    Benchmarks published, archives and learning material given back.

Ready to make your language AI-ready?

We scope the readiness audit first, so you know exactly what data your language needs before recording begins.

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