Table 1. Mean character and word error rates (with 95% CIs) for the handwriting BCI across all 5 days.
“Raw online output” is what was decoded online (in real-time). “Online output + offline language model” was obtained by applying a language model retrospectively to what was decoded online (to simulate an autocorrect feature). “Offline bidirectional RNN + language model” was obtained by retraining a bidirectional (acausal) decoder offline using all available data, in addition to applying a language model. Word error rates can be much higher than character error rates because a word is considered incorrect if any character in that word is wrong.
Character Error Rate [95% CI] | Word Error Rate [95% CI] | |
---|---|---|
Raw online output | 5.9% [5.3, 6.5] | 25.1% [22.5, 27.4] |
Online output + offline language model | 0.89% [0.61, 1.2] | 3.4% [2.5, 4.4] |
Offline bidirectional RNN + language model | 0.17% [0, 0.36] | 1.5% [0, 3.2] |