Word error rate

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Word error rate (WER) is a common metric of measuring the performance of a speech recognition system.

The general difficulty of measuring the performance lies on the fact that the recognized word sequence can have different length from the reference word sequence (supposingly the correct one). The WER is derived from the Levenshtein distance, working at word level instead of character.

This problem is solved by first aligning the recognized word sequence with the reference sequence using dynamic string alignment.

Word error rate can then be computed as:

WER = \frac{S+D+I}{N}

where

  • S is the number of substitutions,
  • D is the number of the deletions,
  • I is the number of the insertions,
  • N is the number of words in the reference.

When reporting the performance of a speech recognition system, sometimes the word recognition rate (WRR) is used instead:

WRR = 1 - WER = \frac{N-S-D-I}{N} = \frac{H-I}{N}

where

  • H is N-(S+D), the number of correctly recognised words.

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