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Multi-Model Transcription with LLM Reconciliation
Anyone who uses voice-to-text knows the frustration of watching a technical term get silently replaced with something that sounds similar but means something completely different. "LORAs" becomes "Lauras," and suddenly your transcription is nonsense. In this episode, we explore a practical solution: running audio through multiple transcription services, then using an LLM as a judge to reconcile the outputs into a single accurate transcript. We cover the alignment problem, why model diversity matters more than repetition, and how to build a pipeline that flags only the parts you need to…
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