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julien-c
HF staff
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README.md
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---
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title: CER
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emoji: 🤗
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sdk: gradio
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app_file: app.py
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pinned: false
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tags:
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- evaluate
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- metric
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# Metric Card for CER
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## Metric description
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---
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title: CER
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emoji: 🤗
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colorFrom: blue
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colorTo: red
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sdk: gradio
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app_file: app.py
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pinned: false
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tags:
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- evaluate
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- metric
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description: >-
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Character error rate (CER) is a common metric of the performance of an
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automatic speech recognition system.
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CER is similar to Word Error Rate (WER), but operates on character instead of
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word. Please refer to docs of WER for further information.
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Character error rate can be computed as:
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CER = (S + D + I) / N = (S + D + I) / (S + D + C)
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where
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S is the number of substitutions,
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D is the number of deletions,
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I is the number of insertions,
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C is the number of correct characters,
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N is the number of characters in the reference (N=S+D+C).
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CER's output is not always a number between 0 and 1, in particular when there
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is a high number of insertions. This value is often associated to the
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percentage of characters that were incorrectly predicted. The lower the value,
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the better the
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performance of the ASR system with a CER of 0 being a perfect score.
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---
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# Metric Card for CER
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## Metric description
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