Update README.md

Update description

README.md

@@ -11,6 +11,31 @@ license: apache-2.0
 tags:
 - evaluate
 - metric
+short_description: Normalized Edit Distance (NED)
+description: >-
+  The Normalized Edit Distance (NED) is a metric used to quantify the dissimilarity between two sequences, typically strings, by measuring the minimum number of editing operations required to transform one sequence into the other, normalized by the length of the longer sequence. 
+  The NED ranges from 0 to 1, where 0 indicates identical sequences and 1 indicates completely dissimilar sequences.
+  It is particularly useful in tasks such as spell checking, speech recognition, and OCR. The normalized edit distance can be calculated using the formula:
+  NED = (1 - (ED(pred, gt) / max(length(pred), length(gt))))
+  Where:
+  gt: ground-truth sequence
+  pred: predicted sequence
+  ED: Edit Distance, the minimum number of editing operations (insertions, deletions, substitutions) needed to transform one sequence into the other.
 ---
 # Metric Card for NED
 
+## Metric Description
+
+The Normalized Edit Distance (NED) is a metric used to quantify the dissimilarity between two sequences, typically strings, by measuring the minimum number of editing operations required to transform one sequence into the other, normalized by the length of the longer sequence. 
+The NED ranges from 0 to 1, where 0 indicates identical sequences and 1 indicates completely dissimilar sequences.
+It is particularly useful in tasks such as spell checking, speech recognition, and OCR. The normalized edit distance can be calculated using the formula:
+
+NED = (1 - (ED(pred, gt) / max(length(pred), length(gt))))
+  
+  Where:
+
+gt: ground-truth sequence
+
+pred: predicted sequence
+
+ED: Edit Distance, the minimum number of editing operations (insertions, deletions, substitutions) needed to transform one sequence into the other.