System and method for disambiguation and error resolution in call transcripts

This invention describes a computer program designed to correct errors in transcripts produced by automatic speech recognition (ASR) systems. It takes an initial transcript, potentially generated by one or two different ASR systems, identifies sections where the ASR was uncertain, and then uses machine learning to predict and insert the correct words, creating a more accurate final transcript. The claims specifically narrow the initial transcript generation to involve two machine learning systems, either working sequentially or in parallel.

Why it matters: Filed before the widespread adoption of highly capable Large Language Models (LLMs), which excel at contextual understanding and text correction. These advanced models could significantly improve the accuracy and efficiency of the proposed error resolution process.

Status: Not in forceListed as no longer active. The specific reason is not in the record we hold.
How hard to build: SpecializedMachine learning models, software logic, data processing.

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