For languages that don't use the Latin (English) alphabet, e.g., Arabic, Hindi, Punjabi, Sinhala, typing can be challenging as keyboards/keypads often default to Latin characters. That makes creating content in these vernacular languages difficult. With transliteration you can create content in these languages using your Latin keypad.
For instance, you type a word on the Latin keypad the way you would pronounce it in Punjabi, and using transliteration you can convert that into Punjabi. It transforms a word from one alphabet to the other phonetically.
- Off-the-shelf Models: Use our pre-trained production-ready models through APIs and integrate them in any application.
- Language Support: Our baseline models support over 40 language pairs including Arabic and 11 Indian languages.
- Train Your with AutoNLP: Use our AutoNLP to improve or build custom transliteration models with your own data for any language.
- Accelerate Dataset Creation with our Data Studio: Equipped with handy utility tools such as phonetic typing, our Data Studio is an in-browser text editor for creating datasets.
- Easy to Integrate and Scale (coming soon): Scale or replicate your deployed models for higher availability and throughput and integrate them with your application through REST APIs.
👉 Quickstart: Getting started instructions to guide you through building your First Transliteration model in under 15 minutes.
Build use-cases via tutorials
👉 Tutorials: Explore tutorials on real-world datasets for practical use-cases.
Integrating with Google Maps, Spotify, and other APIs
If you have tried integrating Google Maps or Spotify APIs with your chatbots in, e.g., Tamil, Arabic, Chinese or Greek, you know they rarely produce acceptable results.
With Transliteration you can extract entities like names, addresses, songs, etc. in your local language and convert them into the Latin (or English) alphabet to fully utilize APIs from Google Maps, Spotify and others.
Creating NLU Data for Chatbots
A common practice is to create a dataset in English and translate it to another language using Google Translate or similar APIs. While this can work well for simple FAQ chatbots, contextual chatbots require well structured/meaningful data in the local languages. Transliteration-powered typing tools can help accelerate the dataset creation process for chatbots in languages that don’t use the Latin (or English) alphabet.
Low-Cost Content Accessibility in Multiple Languages
Internationalization/Translation can be extremely expensive when your databases are in English and dynamic, ever expanding with content like songs, albums, or addresses. Transliteration can be a handy tool to convert such content on the fly to other languages that don’t use the Latin (or English) alphabet. It can be indexed using popular frameworks like Elasticsearch, or other similar tools and instantly made accessible in multiple languages. This can potentially save thousands of dollars on manual translation efforts.
Something as simple as typing can be extremely challenging when we talk about languages spoken in the Middle East, Africa, India and South East Asia. With governments and financial institutions mandating inclusion and content creators being more used to the Latin letter keypad, a tool like Transliteration can be very handy to make it easy to create local language content.