Multi-Intent Matrix Collision Detection in Voice Response Systems
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Solution Overview
Problem
Voice response systems often generate inaccurate responses to human callers due to collisions between similar intents with high accuracy probabilities, leading to unsatisfactory interactions.
Innovation Solution
A method utilizing a multi-intent matrix that translates human voice queries into text strings, analyzes them with adjustable parameters, and re-maps the queries to accurately determine the intended intent by altering parameter settings based on custom values to differentiate between colliding intents, thereby providing a more accurate response.
Engineering Contradictions & Design Principles
Engineering Contradiction Analysis
1Measurement precision
If the voice response system uses a multi-intent matrix to determine caller intent with high accuracy probabilities, then the response accuracy improves, but collisions between similar intents occur leading to inaccurate responses
Solution Approach 1:
The system dynamically adjusts parameter settings (such as probability thresholds, weighting factors, and scrutiny levels) based on the detected collision between intents. When a collision is identified, the system modifies parameters to re-evaluate and differentiate between the colliding intents, thereby resolving the contradiction between high measurement precision and response reliability.
2Measurement precision
If the system analyzes text strings with multiple parameters and custom values to differentiate intents, then collision detection improves, but system complexity increases
Solution Approach 1:
The system pre-configures multiple parameters and custom values for intent analysis before actual query processing. By preparing the analytical framework in advance, the system can efficiently detect and resolve intent collisions without encountering complexity during real-time operation, as the parameter structure is already established and optimized.
3Measurement precision
If the voice response system re-maps queries multiple times with adjusted parameters to resolve collisions, then intent determination accuracy improves, but processing time increases
Solution Approach 1:
The system employs periodic re-mapping with adjusted parameters only when collisions are detected, rather than continuously re-evaluating all queries. This periodic intervention approach maintains high intent determination accuracy for colliding intents while minimizing unnecessary processing time for clear-cut cases, thus resolving the contradiction between precision and time loss.
Data Source
AI summary
A method for utilizing a multi-intent matrix is provided. The method may be used to avoid a derived intent collision while determining correct intent of a human-voice-telephone query. The method may include receiving a telephone call at the voice response system. The method may include responding to the telephone call at the voice response system. The response may include prompting a human caller to utter a reason for the telephone call. The human caller may be associated with the telephone call. The method may include receiving a human-voice-telephone-query-utterance at the voice response system. The method may include translating the human-voice-telephone-query-utterance into a text string. The translating may occur at the voice response system or a translation module. The method may include analyzing the text string utilizing a group of parameters. The method may include re-analyzing the text string utilizing a group of parameters set to custom values.