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---
title: Normalized Edit Distance
emoji: 📈
colorFrom: blue
colorTo: red
sdk: gradio
sdk_version: 4.44.0
app_file: app.py
pinned: false
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. |