Longscribe has introduced a new feature allowing users to ask questions about their transcribed audio, but encountered unexpected engineering challenges. The initial approach of feeding entire transcripts into the LLM failed due to token limits and cost constraints on free tiers, especially for longer recordings. A more effective method involved chunking transcripts based on speaker turns rather than fixed token windows, while preserving timestamps and ensuring answers were strictly grounded in the provided text to prevent hallucination. AI
IMPACT Highlights challenges in applying RAG to unstructured audio transcripts and the impact of free-tier LLM constraints on feature design.
RANK_REASON Product feature launch for a transcription service.
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