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This invention describes a system that automatically analyzes recorded conversations, such as customer service calls, by processing their text transcripts. It uses a machine learning model, trained on examples, to identify and label specific segments of the conversation, like when an interest rate was quoted or if a customer didn't answer a question. Users can define custom labels, and the system then highlights these relevant sections within the transcript for review.
Why it matters: Filed before the widespread accessibility and advanced capabilities of large language models (LLMs). These models could significantly simplify the training of the ML model and enhance the semantic analysis required for custom labeling and complex query processing described in the claims.
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