Localization Today Why Generative AI Still Struggles With Indian Languages
May 9, 2025
Shrushti Chhapia, CEO of A Language World and a council member at the Association of Translation Companies, dives into the hurdles generative AI faces with Indian languages. She discusses data scarcity and the complexities of code-switching that challenge AI models. Shrushti emphasizes the need for inclusive AI to better understand diverse dialects like Bhojpuri, shedding light on efforts aimed at enhancing AI's linguistic capabilities and ensuring better representation for regional languages.
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AI's Struggle with Indian Languages
- AI has made impressive progress in language processing but struggles with many Indian languages.
- The complexity of grammar, idioms, scripts, and cultural nuances in Indian languages poses significant challenges.
Data Scarcity Limits AI Training
- Data scarcity is the main hurdle for AI mastering Indian languages.
- Many regional languages have robust oral traditions but limited digitized textual resources.
Non-Standardized Scripts Challenge AI
- Non-standardized spelling and script variations complicate AI learning for Indian languages.
- Shared scripts with distinct linguistic rules require AI to discern subtle differences accurately.