AI Audio Filtering for Contact Center Agent Protection
Find Innovative SolutionsGenerate Solutions
Solution Overview
Problem
Contact center agents are exposed to negative engagement content, such as angry threats or insults, which can affect their mental health and job performance, and existing de-escalation methods are often ineffective.
Innovation Solution
Implementing AI-driven content filtering systems that analyze audio and visual content during contact center engagements to determine negative emotional states and replace the content with filtered versions, reducing exposure to undesirable interactions.
Engineering Contradictions & Design Principles
Engineering Contradiction Analysis
1Productivity
If contact center agents directly engage with users experiencing negative emotional states, then customer service coverage is maintained, but agent mental health and job performance deteriorate
Solution Approach 1:
The patent introduces an AI model as an intermediary between the user and the agent. The AI model analyzes audio content in real-time during contact center engagements, detects negative emotional states through sentiment analysis, and filters harmful content before it reaches the agent. This mediator protects agents from direct exposure to abusive language, threats, and harassment while maintaining continuous customer service coverage.
2Ease of operation
If traditional de-escalation methods are used to handle negative engagements, then agents attempt to manage difficult situations, but these methods are often ineffective and prolong exposure to harmful content
Solution Approach 1:
The system performs preliminary action by detecting negative emotional states and filtering harmful content in real-time before the agent is fully exposed to it. The AI model continuously monitors audio content during the engagement and proactively blocks abusive language, threats, and harassment speech, reducing the duration and intensity of harmful content exposure while the agent manages the engagement.
3Object-affected harmful factors
If content filtering is implemented to protect agents, then agent wellbeing is improved, but system complexity increases
Solution Approach 1:
The patent replaces complex mechanical or manual content filtering systems with an AI-based sentiment analysis model. The AI model processes audio content using natural language processing and machine learning algorithms to detect negative emotional states, abusive language, threats, and harassment speech. This intelligent system automatically filters harmful content without requiring complex rule-based systems or manual intervention, reducing overall system complexity while maintaining effective protection.
Data Source
AI summary
Audio content filtering is performed to replace audio content initially presented to a contact center agent device from a contact center user device during a contact center engagement. Speech content is obtained at a first device of a contact center agent from a second device of a contact center user during a contact center engagement between the contact center agent and the contact center user. A determination is made, using an artificial intelligence model accessible to the first device, that the speech content meets a threshold. Based on the speech content meeting the threshold, a transcription of the speech content is generated using the artificial intelligence model. The transcription of the speech content is then output in place of the speech content and during the contact center engagement at the first device.