Information about Word Error Rate
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 (supposedly 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:
where
where
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 (supposedly 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:
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.
where
- H is N-(S+D), the number of correctly recognised words.
References
Speech recognition (in many contexts also known as automatic speech recognition, computer speech recognition or erroneously as voice recognition) is the process of converting a speech signal to a sequence of words in the form of digital data, by means of an
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In information theory and computer science, the Levenshtein distance is a string metric which is one way to measure edit distance. The Levenshtein distance between two strings is given by the minimum number of operations needed to transform one string into the other, where an
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