Decoding imagined speech from human brain signals is a challenging and important issue that may enable human communication via brain signals. While imagined speech can be the paradigm for silent communication via brain signals, it is always hard to collect enough stable data to train the decoding model. Meanwhile, spoken speech data is relatively easy and to obtain, implying the significance of utilizing spoken speech brain signals to decode imagined speech. In this paper, we performed a preliminary analysis to find out whether if it would be possible to utilize spoken speech electroencephalography data to decode imagined speech, by simply applying the pre-trained model trained with spoken speech brain signals to decode imagined speech. While the classification performance of imagined speech data solely used to train and validation was 30. 5±4.9 %, the transferred performance of spoken speech based classifier to imagined speech data displayed average accuracy of 26.8±2.0 % which did not have statistically significant difference compared to the imagined speech based classifier (p=0.0983, chi-square =4.64). For more comprehensive analysis, we compared the result with the visual imagery dataset, which would naturally be less related to spoken speech compared to the imagined speech. As a result, visual imagery have shown solely trained performance of 31.8±4.1 % and transferred performance of 26.3±2.4 % which had shown statistically significant difference between each other (p=0.022, chi-square =7.64). Our results imply the potential of applying spoken speech to decode imagined speech, as well as their underlying common features.
|Title of host publication||11th International Winter Conference on Brain-Computer Interface, BCI 2023|
|Publisher||Institute of Electrical and Electronics Engineers Inc.|
|Publication status||Published - 2023|
|Event||11th International Winter Conference on Brain-Computer Interface, BCI 2023 - Virtual, Online, Korea, Republic of|
Duration: 2023 Feb 20 → 2023 Feb 22
|Name||International Winter Conference on Brain-Computer Interface, BCI|
|Conference||11th International Winter Conference on Brain-Computer Interface, BCI 2023|
|Country/Territory||Korea, Republic of|
|Period||23/2/20 → 23/2/22|
Bibliographical noteFunding Information:
This work was partly supported by Institute for Information & Communications Technology Planning & Evaluation (IITP) grant funded by the Korea government (MSIT) (No.2021-0-02068, Artificial Intelligence Innovation Hub; No. 2017-0-00451, Development of BCI based Brain and Cognitive Computing Technology for Recognizing User’s Intentions using Deep Learning).
© 2023 IEEE.
- brain-computer interface
- imagined speech
- speech recognition
- spoken speech
- visual imagery
ASJC Scopus subject areas
- Artificial Intelligence
- Human-Computer Interaction
- Signal Processing