Evaluating OCR Output Quality with Character Error Rate (CER) and Word Error Rate (WER)

#artificialintelligence 

The usual way of evaluating prediction output is with the accuracy metric, where we indicate a match (1) or a no match (0). However, this does not provide enough granularity to effectively assess OCR performance. We should instead use error rates to determine the extent to which the OCR transcribed text and ground truth text (i.e. A common intuition is to see how many characters were misspelled. While this is correct, the actual error rate calculation is more complex than that.

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