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Forecasting weather and forewarning the public with weather alerts help save lives and property immensely. Audio transmissions for alerting are not prone to local infrastructure failure and hence the most dependable. Reception of such alerts should have good clarity of audio. The Mean Opinion Score (MOS) method has traditionally been used in telephony to monitor audio reception quality. It requires an objective skilled listener using a scoring system for feedback used in improving audio quality. However, in weather radio, there is no dedicated listener 24/7. Without listening skills and listener training the MOS scoring could be skewed and of little use. Our paper focuses on the design, building and testing of audio-quality forensics system (AQFS) that uses measurements of network, radio and equipment parameters to monitor audio quality instead of listener feedback. Transmitter stations today have multiple connectivity options and the AQFS can alert the transmission operators to switch to alternate technology during failures. The AQFS also has control features to perform this switching automatically that we have tested. In this paper, we also report our findings, test results and inferences with recommendations. Apart from providing basic but detailed audio quality analysis and comparison of base and transmitted audio using two different mechanisms, the AQFS helped us detect complete audio loss, intermittent audio outages, Specific Area Message Encoding (SAME) Headers, audio anomalies, fades, drops and strange tones which correlate with fading and outage events. The analysis helped at problem transmitter sites in improving audio quality.

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Design and Testing of a Real-Time Audio-Quality Feedback System for Weather Broadcasts and a Framework for a Weather Broadcast Transmission Technology Switch