Cross-subject decoding of imagined speech from scalp EEG: a leakage-controlled evaluation on three public corpora
Why brain signals for imagined speech don't work across different people
Researchers tested whether brain signals from imagined speech could be decoded in one person after training on another person's signals — a requirement for practical brain-computer interfaces that need no calibration. Across three public datasets and 482 pairs of participants, no cross-person transfer survived statistical correction, and what appeared to work within single subjects turned out to reflect brain activity after speech imagery ended, not the imagery itself.
Brain-computer interfaces for speech would be far more practical if they could work on a new user without lengthy calibration. This work shows that imagined speech produces signals too unique to each person to enable that, and reveals that apparent within-subject successes were measuring artifacts rather than true speech imagery — a critical correction that will redirect future research toward either improving signal quality or accepting that personalized calibration is necessary.