Data Augmentation for Edge-AI on-chip Learning

This study applied data augmentation to improve the inference accuracy of edge-artificial intelligence on-chip learning, which uses the fine-tuning technique with limited knowledge and without a cloud server. Subsequently, keyword spotting was adopted as an example of the edge-AI application to evaluate inference accuracy. Investigations revealed that all four data augmentation types contributed to inference accuracy improvements, boosting data augmentation by 5.7 times rather than the one-shot boost without data augmentation recorded previously.