An LLM-based pipeline that applies hand-picked sound effects to generated normal machine audio produces synthetic anomalies whose per-machine-type detection difficulty ranking matches real anomalies, for one autoencoder system.
An effective anomalous sound detection method based on representa- tion learning with simulated anomalies,
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MIMII-Agent: Leveraging LLMs with Function Calling for Relative Evaluation of Anomalous Sound Detection
An LLM-based pipeline that applies hand-picked sound effects to generated normal machine audio produces synthetic anomalies whose per-machine-type detection difficulty ranking matches real anomalies, for one autoencoder system.