Automated Hold Status Detection Using Cue Profiles
Find Innovative SolutionsGenerate Solutions
Solution Overview
Problem
In telephone-based and internet-based transactions, there is a lack of efficient methods for detecting the hold status change from an on-hold state to a live state without constant attention, as existing solutions fail to reliably identify audio cues and metadata due to varying cues between companies and lack of available information about queuing party cues.
Innovation Solution
A system and method utilizing preexisting cue profiles, including audio and text cues, along with a cue metadata database, to determine the hold status by analyzing audio samples and generating a confidence score, with optional verbal challenges for confirmation, employing components like speech recognition engines and audio pattern matching.
Engineering Contradictions & Design Principles
Engineering Contradiction Analysis
1Productivity
If automated services are used to handle transactions, then productivity is improved, but reliability deteriorates due to inability to reliably detect hold status changes
Solution Approach 1:
The system performs preliminary actions by continuously monitoring audio cues and metadata before the hold status change becomes apparent. The cue profile database pre-stores characteristic audio patterns, and the system proactively detects transitions by comparing real-time audio samples against these profiles, enabling automated detection without human intervention.
Solution Approach 2:
The system implements feedback mechanisms by continuously analyzing audio cues and metadata during calls, comparing detected patterns against the cue profile database, and adjusting detection algorithms based on confidence scores. This feedback loop enables the automated system to reliably identify hold status changes and improve detection accuracy over time.
2Reliability
If constant human attention is used to monitor hold status, then reliability is improved, but productivity deteriorates due to loss of time and resources
Solution Approach 1:
The system enables self-service by implementing autonomous detection of hold status changes through automated audio analysis. The cue profile database and detection algorithms operate independently without requiring constant human monitoring, allowing the system to reliably detect status changes while freeing human operators to handle other tasks.
Solution Approach 2:
The system replaces the mechanical system of human monitoring with an automated electronic detection system. Audio cues and metadata are analyzed by speech recognition engines and pattern matching algorithms, substituting human attention with automated technological processes that maintain reliability while improving productivity.
3Productivity
If standardized cue analysis is implemented, then productivity is improved through automation, but measurement precision deteriorates due to varying cues between companies
Solution Approach 1:
The system applies local quality by customizing cue profiles for each company or organization. The cue profile database stores company-specific audio patterns, metadata structures, and detection parameters, allowing the standardized automated system to adapt to local variations in cues while maintaining overall automation efficiency.
Solution Approach 2:
The system performs preliminary configuration by pre-building company-specific cue profiles in the database before deployment. This preliminary action captures organization-specific audio characteristics and metadata formats, enabling the automated detection system to achieve both standardization and precision for each company's unique cues.
Data Source
AI summary
A system and method is provided for detecting a hold status in a transaction between a waiting party and a queuing party. The system is adapted to use a preexisting cue profile database containing cue profile for a queuing party. A preexisting cue profile may be used for detecting a hold status in a call between a waiting party and a queuing party. The cue profile of the queuing party may include audio cues, text cues, and cue metadata. The transaction may be a telephone based, mobile-phone based, or internet based.