Overfitting from Reused Background Noise
If a synthetic audio set keeps reusing the same short recording of fan hum, a model may memorize that hum instead of learning the broader pattern of the task. It can then perform poorly on new recordings that contain different fan sounds. The same risk can appear even when the dataset is large, such as hundreds of hours of audio, if all of it comes from only a few machines; the model may fit those specific sources rather than generalize to new ones.
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Overfitting from Reused Background Noise
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Representativeness of Synthetic Noise Samples
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Overfitting from Reused Background Noise
Synthetic Data Can Still Cause Narrow Memorization
Learn After
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