Add description to card metadata (#1)

- Add description to card metadata (9170004a8d3e9a8ae4d404385c31de084839b19c)

README.md

@@ -1,6 +1,6 @@
 ---
 title: CER
-emoji: 🤗 
+emoji: 🤗
 colorFrom: blue
 colorTo: red
 sdk: gradio
@@ -8,10 +8,44 @@ sdk_version: 3.0.2
 app_file: app.py
 pinned: false
 tags:
-- evaluate
-- metric
----
+  - evaluate
+  - metric
+description: >-
+  Character error rate (CER) is a common metric of the performance of an
+  automatic speech recognition system.
+
+
+  CER is similar to Word Error Rate (WER), but operates on character instead of
+  word. Please refer to docs of WER for further information.
+
+
+  Character error rate can be computed as:
+
+
+  CER = (S + D + I) / N = (S + D + I) / (S + D + C)
+
+
+  where
 
+
+  S is the number of substitutions,
+
+  D is the number of deletions,
+
+  I is the number of insertions,
+
+  C is the number of correct characters,
+
+  N is the number of characters in the reference (N=S+D+C).
+
+
+  CER's output is not always a number between 0 and 1, in particular when there
+  is a high number of insertions. This value is often associated to the
+  percentage of characters that were incorrectly predicted. The lower the value,
+  the better the
+
+  performance of the ASR system with a CER of 0 being a perfect score.
+---
 # Metric Card for CER
 
 ## Metric description