Comments (3)
The percentage there is calculated as count * max(len(gt), len(pred))
for the confusion in question divided by sum(max(len(gt_str), len(pred_str)))
for all the confusions in the dataset. The label "PERCENT" does not really mirror this complexity, I guess... Just calculating the percentage of the count against total_count might be a bit more consistent. On the other hand, the current implementation shows how much of the total CER is actually caused by a particular confusion. Would the label PERCENT_CER be more appropriate?
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Ah, got it! I agree this figure is actually more relevant than simple relative count.
Would the label PERCENT_CER be more appropriate?
Yes, absolutely! That would make it clear immediately.
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completed in 5a46ca1
many thanks!
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Related Issues (20)
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