Contact Center Audio Analysis During Non-Audio Modes
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Solution Overview
Problem
Contact center systems lack effective mechanisms to analyze and utilize audio signals captured by microphones during non-audio communication modes, such as when agents are not actively conversing with individuals, leading to missed opportunities for data capture and analysis.
Innovation Solution
Implementing a system that identifies and analyzes utterances spoken by contact center agents during non-audio modes, generating session metadata, and storing it in contact session records, which can include commands, profanity flags, and sentiment analysis, to facilitate various applications and actions.
Engineering Contradictions & Design Principles
Engineering Contradiction Analysis
1Loss of information
If the microphone is utilized to capture sounds during non-audio communication modes, then audio data is captured and analyzed for performance evaluation and quality assurance, but system complexity increases due to the need for audio analysis processing during inactive periods
Solution Approach 1:
The system performs preliminary classification of audio signals during non-audio modes to identify utterances before full analysis. This preliminary action filters out irrelevant sounds and prepares only significant audio segments for detailed processing, reducing overall system complexity while maintaining comprehensive audio data capture capability
Solution Approach 2:
The system extracts only the necessary audio segments containing utterances during non-audio communication modes, separating them from the continuous audio stream. This extraction approach captures valuable audio information while avoiding the complexity of processing entire audio streams, focusing resources only on relevant data
2Loss of information
If audio analysis is performed during non-audio modes, then valuable metadata is generated for performance evaluation, but processing time and computational resources are consumed during periods when the agent is not actively communicating
Solution Approach 1:
The system implements periodic audio analysis during non-audio modes rather than continuous processing. It analyzes audio signals at scheduled intervals or when specific conditions are met (such as detecting potential utterances), generating necessary metadata while minimizing unnecessary processing time and computational resource consumption during agent idle periods
3Loss of information
If the system distinguishes between audio and non-audio modes, then audio analysis is applied selectively to improve relevance, but the difficulty of detecting and measuring communication mode increases
Solution Approach 1:
The system uses feedback from the communication platform to automatically determine whether the agent is in audio or non-audio mode. By monitoring the active communication channel and agent status information, the system selectively applies audio analysis only during non-audio modes, improving analysis relevance while avoiding the complexity of implementing complex mode detection algorithms
Data Source
AI summary
Microphone monitoring and analytics are provided. An initiation of a new contact session is determined that includes a communication interaction between a contact center agent (CCA) having a microphone and a contacting individual (CI). Prior to an end of the new contact session, a non-audio mode wherein audio signals received by the microphone are not communicated to the CI is determined. Audio signals received via the microphone during the non-audio mode are analyzed. An utterance spoken by the CCA is identified. Contact session metadata is generated based on the utterance. A contact session record that includes the contact session metadata is generated. The contact session record is stored.