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Machine learning tool aims to detect live humans on phone calls

A machine learning project aims to develop a tool that can distinguish between live human agents and automated messages on outbound phone calls. The system will analyze audio streams in real-time, classifying sounds like music, recorded announcements, and human speech within seconds. The goal is to save users time by identifying when a call has been successfully connected to a person, rather than an automated system or voicemail. AI

IMPACT This project could improve user experience by reducing time spent on automated phone systems.

RANK_REASON The cluster describes a research project and its proposed methodology for an audio classification application. [lever_c_demoted from research: ic=1 ai=1.0]

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COVERAGE [1]

  1. r/MachineLearning TIER_1 · /u/Bucky102 ·

    Live Human Detector on Outbound Phone Calls [R]

    <!-- SC_OFF --><div class="md"><p><strong>Goal</strong><br /> To save humans wasting time sitting in Call Centre queues waiting to be answered</p> <p>To have tool listen in on the audio stream of a live call, post IVR Navigation - to determine whether the call has transitioned ou…