Call Queue Voice Segment Analysis for User Alerting
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Solution Overview
Problem
Users waiting for staff services at call centers often experience long wait times and boredom due to repetitive prompt tones, and existing AI technologies may fail to understand user issues or provide adequate solutions, leading to a need for improved call management to enhance user experience.
Innovation Solution
A method that records voice segments from call centers, identifies predefined wait tones, adjusts device volume during wait times, and alerts users when a staff member becomes available, allowing them to attend to their service promptly.
Engineering Contradictions & Design Principles
Engineering Contradiction Analysis
1Reliability
If users wait in queue for call center service, then they can receive staff assistance, but they experience long wait times and boredom
Solution Approach 1:
The system performs preliminary actions by detecting staff availability status continuously during the wait queue and proactively alerting users before they need to engage with staff. The volume adjustment and alert mechanisms are prepared in advance to notify users immediately when service becomes available, reducing the effective wait time experience.
Solution Approach 2:
The system implements feedback by continuously monitoring the call center's voice segments for staff availability indicators and providing real-time feedback to users through alerts and volume adjustments. This closed-loop feedback mechanism keeps users informed about their service status without requiring constant attention to repetitive prompt tones.
2Loss of information
If users monitor call center announcements continuously, then they can detect staff availability, but they cannot perform other tasks during wait time
Solution Approach 1:
The system performs self-service by automatically monitoring and analyzing call center voice segments for staff availability without requiring user intervention. The automated detection, volume adjustment, and alerting functions operate independently, freeing users to perform other tasks while the system handles information gathering and notification autonomously.
Solution Approach 2:
The system replaces the mechanical requirement for continuous user attention with automated electronic monitoring and detection mechanisms. Voice segment analysis algorithms substitute for human listening, and automated alert systems replace the need for users to actively monitor announcements, enabling multi-tasking during wait times.
3Ease of operation
If call centers use repetitive prompt tones to manage queues, then they can guide waiting users, but users experience boredom and disengagement
Solution Approach 1:
The system extracts the valuable information function from the repetitive prompt tones by specifically detecting voice segments related to staff availability while filtering out the boring repetitive content. Users only need to respond to meaningful alerts about service availability rather than continuously attending to all prompt tones, eliminating boredom while maintaining queue management effectiveness.
Solution Approach 2:
The system applies local quality by selectively adjusting volume and providing alerts only for specific meaningful voice segments related to service availability, rather than treating all prompt tones uniformly. This targeted approach maintains the necessary queue management communication while eliminating the harmful repetitive elements that cause user disengagement.
Data Source
AI summary
Embodiments of the invention provide methods, systems, computer program products for managing a call waiting in a queue during a request for staff services provided by a call center. According to the method, a first voice segment received in a call made by a device is recorded first. Next, whether a part of the first voice segment is related to a first predefined voice segment is determined. The volume of device is adjusted in response to the part of the first voice segment being related to the first predefined voice segment. A user of the device is alerted in response to the part of the first voice segment being not related to the first predefined voice segment.