How Ceıvır Saves Names: OCR, Unicode, and Keyboard Fixes for Turkish

ceıvır The Practical Guide to Transliteration, Localization, and Preserving Turkic Scripts

Introduction 

Ceıvır is a concept and toolset for accurate text conversion and Latin-Turkic conversion, designed to handle tricky cases like the Turkish dotless ı handling, keyboard mapping differences, and Unicode normalization. Whether you’re a developer, language activist, or daily user frustrated by broken text, ceıvır promises a reliable transliteration tool, mobile app, browser extension, and open-source ecosystem for multilingual content and preservation.

What is ceıvır and what does it do?

At its core, ceıvır is a transliteration tool and localization platform that converts text between scripts and canonical orthographies while preserving accents and meaning. It focuses on practical problems:

• Correctly converting dotted/dotless characters between keyboards and encodings.

• Normalizing Unicode so copy-paste across platforms doesn’t break names or grammar.

• Providing keyboard layouts and browser extensions for smooth typing.

• Offering OCR transliteration and speech-to-text to capture analog texts and spoken heritage.

Imagine you copy a Turkish sentence from an older PDF, paste it into a chat, and the dotless ı becomes a standard i — meaning changes and names get mangled. Ceıvır fixes that by applying orthography rules and Unicode normalization before displaying or exporting.

Why dotless ı handling matters

Small letters can mean big errors. The Turkish dotless ı vs dotted i is a classic example where a single glyph changes pronunciation and meaning. Ceıvır’s dotless ı handling includes:

• Language-aware detection to choose the right glyph.

• Keyboard mapping that maps Latin-key input to proper Turkish output.

• Fallbacks for legacy encodings and corrupted text.

This is crucial not only for everyday messages but for cultural heritage digitization where preserving proper names keeps historical records accurate.

Key features: browser extension, mobile app, API, and offline mode

Ceıvır aims to cover multiple user needs with distinct modules:

Browser extension

• Fix text on webpages in real time.

• Provide instant keyboard mapping and spellcheck.

• Works with screen readers to improve accessibility.

Mobile app

• Local keyboard layouts and autocorrect for Turkish and related Turkic languages.

• Offline mode conversion for privacy and low-bandwidth usage.

API and GitHub

• Open-source core on GitHub so developers can audit, contribute, or host their own instance.

• REST API for integrating ceıvır into apps, CMS, wikis, or transcription services.

OCR and speech

• OCR transliteration pipelines convert scans into normalized text.

• Speech-to-text modules feed into machine translation or archival databases.

These building blocks let editors, libraries, and developers adapt ceıvır for publishing, subtitles, or automated transcription.

Technical approach: Unicode normalization, NLP, and datasets

Ceıvır blends rule-based orthography with machine learning. The technical stack typically includes:

• Unicode normalization to unify different code points representing the same glyph.

• NLP models trained on curated datasets to predict proper casing, accents, and contextual glyphs.

• Spellcheck and grammar rules derived from authoritative references like the Turkish Language Association (TDK).

• Training datasets built from open sources (Wikipedia, public corpora) and community contributions to avoid bias.

This hybrid approach improves transliteration accuracy while keeping behavior predictable for editors and publishers.

Integration and developer-friendly APIs

Developers can integrate ceıvır via:

1. A public REST API for on-the-fly conversion (suitable for websites and chat services).

2. A client library and containerized server available on GitHub for self-hosting.

3. Plugins for content platforms and editors (CMS, subtitle tools) to automate normalization before publishing.

Leveraging a GitHub repo allows transparency — contributing to the open-source project helps the tool improve while allowing institutions to run private instances for sensitive archives.

Community contributions, open-source, and ethical data sourcing

Community involvement is critical for language tools. Ceıvır encourages:

• Crowdsourced corrections and annotation to improve NLP for minority languages.

• Partnerships with academic institutions (MIT Media Lab-style research collaborations) to validate models.

• Compliance with ethical guidelines from organizations like UNESCO for language preservation.

Open sourcing the core ensures that projects can audit data usage, avoid proprietary lock-in, and keep the tool aligned with community needs.

Accessibility, screen readers, and cultural preservation

Language tools must be accessible. Ceıvır includes features for:

• Screen reader compatibility so visually impaired users get correct pronunciations.

• Subtitles and closed-caption normalization for multilingual content sharing on platforms like YouTube or Spotify-hosted podcasts.

• Interfaces that respect dialectical variations and preserve cultural naming conventions.

This matters for educational content and for communities relying on digitized archives.

Privacy and offline mode: protecting sensitive texts

Many historical or personal texts can’t be uploaded to third-party services. Ceıvır addresses this with:

• An offline mode conversion in the mobile and desktop clients.

• Local-only API keys for on-premise usage, suitable for libraries or government archives.

• Clear privacy policies and avoidance of sending raw text to external ML services like OpenAI unless explicitly authorized.

These safeguards let cultural institutions use the tool without risking exposure of sensitive materials.

Real-life example: cleaning a family archive

Imagine a family archive of scanned letters written in Ottoman-influenced Turkish. OCR yields messy Latin text where names and diacritics are lost. Using ceıvır’s OCR transliteration plus orthography rules, volunteers convert those scans into searchable, normalized text that preserves names correctly, enabling genealogists and local historians to restore context and meaning.

Roadmap and partnerships

A successful ceıvır project often partners with:

• TDK for authoritative orthography.

• Platform partners (Google and Apple) to distribute keyboards via Play Store and App Store.

• Research bodies like MIT Media Lab or Mozilla for privacy-focused implementations.

• Content hubs like Wikipedia for dataset enrichment and public access.

These partnerships speed adoption and ensure the tool fits real editorial and educational workflows.

Conclusion 

Ceıvır bridges a practical need: keeping text accurate across devices, encodings, and time. By combining Unicode normalization, NLP, OCR, and community-driven datasets, ceıvır helps preserve language, improve accessibility, and make multilingual publishing smoother. Want a tailored plan to deploy ceıvır in your archive, newsroom, or app? Tell me your platform and I’ll sketch a 30-day integration roadmap.

FAQ — (answers to the PAA questions)

What is ceıvır and what does it do?
Ceıvır is a transliteration and localization tool that handles tricky cases like dotless ı handling, Unicode normalization, keyboard mapping, OCR transliteration, and speech-to-text to preserve accurate text in Turkic languages.

How accurate is ceıvır for dotless ı handling and transliteration?
Accuracy depends on hybrid methods: rule-based orthography (informed by TDK) plus NLP trained on curated datasets. For modern Turkish and related languages, accuracy is high; legacy texts require OCR cleanup and community correction.

Can developers integrate ceıvır via an API or GitHub repo?
Yes. Ceıvır provides an open-source core on GitHub and a REST API for on-the-fly conversion. Organizations can self-host containers for privacy-sensitive workflows.

Is ceıvır available as a mobile app or browser extension?
Typically yes — ceıvır offers keyboard mapping via mobile apps on Google Play and App Store, and browser extensions for real-time webpage normalization.

How does ceıvır protect privacy and support language preservation?
Ceıvır supports offline mode and on-premise deployments, minimizes outbound data, and encourages community-driven datasets and partnerships with academic and cultural organizations like UNESCO.