Audio Conversation Annotation via Engagement Intelligence Platform

The patent replaces manual human review of audio conversations with an automated machine-learning-based system. The EIP transcribes audio to text and uses ML models to automatically identify states, entities, and relationships, eliminating the need for human reviewers to listen to entire conversations while maintaining high search accuracy through intelligent automated analysis.

The system creates a textual copy (transcript) of the audio conversation and analyzes this copy using machine learning models. This copying approach allows the system to process conversations quickly without requiring human review of the original audio, significantly reducing time consumption while maintaining search precision through the intelligent processing of the text representation.

The patent transforms the search approach by changing from simple text keyword matching to a multi-parameter analysis system. The EIP identifies and extracts multiple parameters including states, entities, relationships, and contextual information using machine learning models, enabling both fast search execution and high accuracy for nuanced queries through sophisticated parameter-based filtering and matching.

The system segments the conversation analysis into distinct components: transcribing audio to text, identifying states, extracting entities, and establishing relationships. This segmentation allows each component to be optimized independently, with the text transcription providing speed and the ML-based state/entity/relationship analysis providing precision, achieving both fast and accurate search results.

The patent introduces machine learning models as intermediary components between the raw audio/text and the search queries. These ML models act as mediators that automatically interpret nuanced information, extract meaningful patterns, and prepare data structures that can answer complex queries, enabling the system to capture nuanced information without requiring overly complex search interfaces or manual processing.

The system performs preliminary analysis by automatically transcribing audio to text and pre-processing the data to identify states, entities, and relationships before actual search queries are executed. This preliminary action prepares the conversation data in an optimized format that enables both simple and nuanced searches to work effectively, reducing the need for complex search mechanisms while maintaining high information capture capability.