Techniques for detecting anomalies in audio recordings for predictive maintenance
AssigneeDisney Enterprises, Inc.
InventorsSarah Josephine PAGANO, Amber Elizabeth PAULSEN, Jeremy EATON, David MACLEAN, Isabelle Victoria WANG
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Abstract
A computer-implemented technique for detecting audio anomalies includes processing a first frequency representation of a first audio recording using a first trained machine learning model to generate a second frequency representation of at least one voice and a third frequency representation of at least one sound produced by an equipment; detecting, using a second trained machine learning model, an anomaly based on the third frequency representation; and transmitting an alert to at least one computing device based on the anomaly.
Claims20
A computer-implemented method for detecting audio anomalies, the method comprising:
- processing a first frequency representation of a first audio recording using a first trained machine learning model to generate a second frequency representation of at least one voice and a third frequency representation of at least one sound produced by an equipment;
- detecting, using a second trained machine learning model, an anomaly based on the third frequency representation;
- and
- transmitting an alert to at least one computing device based on the anomaly.
One or more non-transitory computer-readable media storing instructions that, when executed by at least one processor, cause the at least one processor to perform the steps of:
- processing a first frequency representation of a first audio recording using a first trained machine learning model to generate a second frequency representation of at least one voice and a third frequency representation of at least one sound produced by an equipment;
- detecting, using a second trained machine learning model, an anomaly based on the third frequency representation;
- and
- transmitting an alert to at least one computing device based on the anomaly.
A system, comprising:
- a memory storing instructions;
- and
- one or more processors, that when executing the instructions, are configured to perform the steps of:
- processing a first frequency representation of a first audio recording using a first trained machine learning model to generate a second frequency representation of at least one voice and a third frequency representation of at least one sound produced by an equipment,
- detecting, using a second trained machine learning model, an anomaly based on the third frequency representation, and
- transmitting an alert to at least one computing device based on the anomaly.
Dependencies are inferred from the claim text.