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Add description to card metadata (#1)

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- Add description to card metadata (9170004a8d3e9a8ae4d404385c31de084839b19c)

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  1. README.md +38 -4
README.md CHANGED
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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
@@ -8,10 +8,44 @@ sdk_version: 3.0.2
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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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- ---
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
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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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+
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+
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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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+
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+
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+ Character error rate can be computed as:
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+
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+
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+ CER = (S + D + I) / N = (S + D + I) / (S + D + C)
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+
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+
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+ where
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+
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+ S is the number of substitutions,
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+
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+ D is the number of deletions,
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+
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+ I is the number of insertions,
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+
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+ C is the number of correct characters,
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+
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+ N is the number of characters in the reference (N=S+D+C).
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+
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+
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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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+
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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