Text and Speech Analysis

Through speech and text analysis, our models identify not just what is said, but how it’s said — detecting emotional tones, pauses, emphasis, and rhythm that reveal subtle cues about wellbeing.
We also analyze local expressions and proverbs to capture emotional meaning embedded in culture.

In short: we teach machines to listen with context, not just transcribe.

Natural Language Processing

Once transcribed, GENSCORE’s NLP engine goes beyond word-level understanding.
It interprets idioms, figurative speech, and culturally specific phrases that traditional AI often misreads.
For instance, when someone says “my body no too dey ginger” or “the world don full for my head,” our models learn that these are expressions of emotional distress, not literal descriptions.

This step makes our system linguistically and culturally adaptive — ensuring that language diversity becomes a source of insight, not bias.

Human-in-the-Loop

we believe technology should support, not replace, human judgment.
That’s why our pipeline integrates experts — clinicians, linguists, and cultural psychologists — who review, validate, and refine the AI’s interpretations.
This collaboration ensures that every model decision remains grounded in real-world understanding and ethical oversight.

Our AI learns from experts’ corrections, creating a continuous partnership between human wisdom and machine learning.

Feedback and Community Loop

Innovation doesn’t stop at model deployment.
Through GENCURATE, contributors and transcribers provide ongoing data that captures evolving linguistic patterns, emotional expressions, and community realities.
Every new input helps fine-tune our models — improving accuracy, fairness, and relevance over time.

It’s a living system that learns with communities, not about them.