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  • 1.  Understanding AI Scoring Limitations for Acoustic and Time-Based Behaviors

    Posted yesterday

    Hi everyone,

    I've been deep-diving into AI Scoring (Virtual Supervisor) lately, specifically trying to automate the evaluation of time-sensitive behaviors, such as the "Initial Greeting within 10 seconds" or "Excessive Hold/Silence" thresholds.

    After some testing and verification, I wanted to share a key finding and start a discussion on how you are handling these scenarios.

    The Challenge: It appears that the AI Scoring engine currently evaluates the transcript (textual content) rather than the interaction's metadata or acoustic timestamps. The Impact: When setting a rule like "Agent must greet within 10 seconds," we encountered false positives. If a customer (External Participant) speaks first-even to complain about the wait-the AI might interpret that initial voice activity as a "prompt greeting," failing to distinguish that the agent (Internal Participant) remained silent. Since the LLM doesn't "see" the 10-second clock, it focuses on the flow of the conversation rather than the literal duration of silence.

    Our Current Conclusion:

    • AI Scoring is excellent for sentiment, empathy, and script compliance (intent).

    • Speech Analytics (Programs/Topics) or Acoustic Metrics remain the correct tools for measuring exact silence duration, dead air, or specific timestamp-based KPIs.

    Questions for the community:

    1. Have you found a way to "prompt" the AI Scoring Help Text to better recognize participant-specific delays without metadata access?

    2. Are you moving all time-based compliance (like the 10s greeting rule) back to traditional Speech Analytics topics, or are you redefining your Quality Forms to measure "Proactivity" instead of "Seconds"?

    Looking forward to hearing how you are balancing AI-powered evaluations with acoustic reality!

    Best regards,

    Rick!


    #AIScoring(VirtualSupervisor)

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    Ricardo Solano
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  • 2.  RE: Understanding AI Scoring Limitations for Acoustic and Time-Based Behaviors

    Posted 8 hours ago

    Hi! 

    Interesting topic and interested to see peoples findings. 

    We have been unable to get the times right, same as you. We have actually used interaction categories to detect acoustic metrics according to guidelines. Your specific "Agent greeting happens 10 seconds to start of the phone call" can be detected via topics easily to interaction category. 
    Of course, if you want this in an evaluation, maybe test if AI can detect if an interaction category is found on the interaction? My wild guess is that no but you never know :) 




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    Viivi Tiainen
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    Original Message


  • 3.  RE: Understanding AI Scoring Limitations for Acoustic and Time-Based Behaviors

    Posted 5 hours ago

    My understanding is that AI scoring bases it's responses 100% on the words in the transcript itself, so will not pick up on acoustics, pace or tone. 



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    Heather Henderson
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    Original Message


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