Word error rate
Word error rate is the ratio of word-level substitutions, deletions, and insertions required to transform a recognized transcription into a reference transcription.
Sutskever's List
Word error rate is the proportion of word-level recognition errors, typically computed from substitutions, deletions, and insertions relative to a reference transcript.
- How it is used
- Evaluates speech-recognition systems by comparing word-level errors across datasets and against human performance.
- How deep it goes
- Defines the error proportion and compares reported results, but does not derive alignment procedures or calculation details.
- Examples
- Uses WSJ, LibriSpeech, VoxForge, and CHiME results to compare DS2 with human listeners.
- What you can do after
- Evaluate speech-recognition quality across datasets and identify when environmental conditions widen the human–system gap.
Natural Language Processing in Action, Second Edition
Word error rate is the proportion of word-level transcription errors relative to the reference transcription.
- How it is used
- Evaluates and compares automatic speech-to-text accuracy when selecting a system for a voice assistant.
- How deep it goes
- Defines word-level transcription comparison and reports benchmark results, but does not detail the calculation procedure.
- Examples
- Uses AI, phone, meeting, video, and finance benchmark datasets to compare Kaldi, wav2vec 2.0, and Whisper.
- What you can do after
- Evaluate STT systems using benchmark WERs and compare their performance across deployment-relevant speech domains.
Read how Natural Language Processing in Action, Second Edition explains word error rate →
Related concepts
- speech recognitionmeasures · Speech recognition is the computational conversion of spoken language from audio into a machine-readable representation, typically text.
- Deep Speech 2measures · Deep Speech 2 is a large-scale neural speech-recognition system designed for end-to-end automatic speech recognition.
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