Cultural Narrative Preservation

We combine computational experiments and ethnographic fieldwork to preserve endangered languages and cultural narratives.

Community Engagement

Partnering with indigenous communities to record oral narratives while prioritizing consent and co-ownership protocols.

Model Training

Utilizing GPT-4’s fine-tuning API to enhance understanding of endangered languages and cultural contexts.

The mixed-methods approach truly captures the essence of our cultural narratives, ensuring authenticity and respect in every interaction. A transformative experience for all involved.

The study adopts a mixed-methods approach combining computational experiments, ethnographic fieldwork, and participatory design.

Data Collection: Partner with Indigenous communities in Southeast Asia and the Americas to record oral narratives (myths, songs, rituals) in their native languages. Consent and co-ownership protocols will be prioritized.

Model Fine-Tuning: Use GPT-4’s fine-tuning API to train the model on three datasets:

Linguistic Corpus: Texts in endangered languages (e.g., Ainu, Quechua).

Cultural Context: Anthropological metadata (e.g., ritual symbolism, social hierarchies).

Community Feedback: Iterative input from cultural custodians to refine outputs.

Evaluation:

Quantitative: Measure transcription accuracy, semantic coherence, and cultural relevance via metrics like BLEU-score and community-defined rubrics.

Qualitative: Conduct interviews and focus groups with community members to assess perceived authenticity and usability.