From the source
In the diverse linguistic landscape of India, English to Indic language translations play a crucial role in knowledge sharing and consumption.
While translation technologies have existed for years, a significant gap has persisted between formal translations and the way Indians actually communicate in their daily lives, leaving most knowledge lost in translation.
Existing translation models, have long struggled with the nuances of colloquial language, regional expressions, and the unique phenomenon of code-mixing that characterizes Indian multilingualism.
In India, where most people are bilingual, spoken language often mixes words from English and regional languages.
Colloquial language differs vastly from formal language in the Indian context and varies across dialects.
Existing translation models, trained primarily on formal sources like newspapers and books, don't represent how Indians actually communicate.
Sarvam's translation model is trained on real-world formal and colloquial communication data, making translations closer to everyday speech.
Conventional models fall short in several aspects: …
