NagaTranslate: Building a translation and voice pipeline for low-resource Nagaland creoles (Whisper, VITS, LLMs) [P]

Short summary

Engineer shares NagaTranslate architecture for low-resource Naga languages, using fine-tuned Whisper/VITS for speech and commercial LLM APIs for translation. Key challenges: bridging quality gaps with self-hosted models, handling spelling variations, and tuning for regional accents on limited voice data. Seeks community advice on resource-constrained NLP architectures.

• •Built translation + speech pipeline for Nagamese, Ao, Sema—languages with minimal digital data
• •Evolved from fine-tuned NLLB to commercial LLM APIs for better colloquial flow; long-term goal is lightweight self-hosted models
• •Open technical questions on bridging API→self-hosted quality gaps, handling spelling variants, and accent robustness with scarce voice data

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