Developer Tests Newspaper-Trained AI to Better Transcribe Barbados-Specific Audio

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A developer experimented with improving speech recognition accuracy for Barbados-specific content by fine-tuning the Qwen3-Omni audio model using a 51.6-million-token archive of local newspapers. The project was motivated by errors in existing models, such as GPT Transcribe mishearing the event name 'Rise Together' as 'Rice Together,' highlighting how unfamiliar local proper nouns trip up general-purpose AI. The domain-adaptive pretraining run was stopped early at step 500 of a planned 801 steps, meaning results are preliminary and based on an incomplete corpus. The adapted model scored higher on a Barbados-specific knowledge probe, especially for local people and institutions, but performed slightly worse on general-knowledge questions. Crucially, the team has not yet verified whether the changes translate into more accurate audio transcription, and further testing is planned.

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