Real-Time Speech Analysis for Dynamic Call Center Referral Interfaces
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Solution Overview
Problem
Conventional methods for generating professional profiles and identifying suitable referrals in call centers are often manual, time-consuming, and unable to keep pace with the velocity, volume, and variety of data, leading to intuition-driven matching rather than data-driven, bias-free identification of appropriate physicians for patient needs.
Innovation Solution
A system that analyzes speech during calls to extract patient data, determines requirements, and generates potential referrals to physicians with matching profiles, dynamically modifying the user interface to display these referrals in real-time, using an analysis engine to identify patient needs and match them with suitable physicians based on profile data.
Engineering Contradictions & Design Principles
Engineering Contradiction Analysis
1Productivity
If manual methods are used to generate professional profiles and identify referrals, then the process can be controlled and reviewed, but it is time-consuming and cannot keep pace with the velocity, volume, and variety of data
Solution Approach 1:
The system performs self-service by automatically analyzing speech data, extracting patient information, determining requirements, and generating referrals without requiring manual intervention. The analysis engine autonomously processes data from multiple sources and updates professional profiles in real-time, eliminating the need for manual data collection and processing while maintaining high productivity.
Solution Approach 2:
The patent replaces manual mechanical processes with automated digital systems. Instead of manual data collection and analysis, the system uses speech recognition technology, automated data extraction, and computational algorithms to process information at high speed, thereby increasing productivity while reducing manual labor.
2Measurement precision
If conventional manual methods are used, then the process is simple and controllable, but it relies on operator intuition and limited record-keeping capabilities
Solution Approach 1:
The system segments the complex data processing task into distinct functional modules: speech recognition module for capturing patient information, data extraction module for identifying key details, analysis module for determining patient requirements, and matching module for selecting appropriate physicians. This segmentation allows each component to specialize in specific tasks, improving overall accuracy while managing complexity through modular architecture.
Solution Approach 2:
The patent introduces an intermediary analysis engine that acts as a mediator between raw speech data and final referral decisions. This intermediary layer processes and interprets unstructured speech data, extracts meaningful information, and translates it into structured requirements for matching, thereby improving accuracy without directly exposing the user to system complexity.
3Speed
If real-time speech analysis is performed during calls, then referral identification speed increases, but data processing complexity and computational requirements increase
Solution Approach 1:
The system performs preliminary actions by pre-processing speech data and extracting key information during the call itself, rather than waiting for the call to end or requiring subsequent batch processing. The analysis engine continuously monitors speech input, identifies patient requirements in real-time, and updates professional profiles immediately, enabling fast response speed through proactive data processing.
Solution Approach 2:
The patent implements dynamic processing where the analysis engine adapts its operations based on real-time call progress and data availability. The system dynamically adjusts the depth and scope of analysis based on what information has been gathered so far, allowing real-time responses while managing computational complexity by only processing necessary data at each moment rather than analyzing everything simultaneously.
Data Source
AI summary
A method for analyzing speech generated during a call to generate a potential referral and automatically modifying, during the call, a user interface displaying data associated with the analyzed speech, includes analyzing, by an analysis engine, during a call by a patient to a call center operator, data generated during the call, the data received from a second computing device. The method includes identifying patient data associated with the patient. The method includes determining at least one requirement of the patient based upon the identified patient data and the analysis. The method includes generating a potential referral to a physician for the patient, the physician having a profile that satisfies the determined at least one requirement. The method includes modifying a user interface displayed to the call center, during the call, the modification to the display including addition of an identification of the potential referral.