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 %, the transferred performance of spoken speech based classifier to imagined speech data displayed average accuracy of 26.8 % 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 % and transferred performance of 26.3 % 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.
翻译:从人类大脑信号中解析想象中的言语是一个具有挑战性和重要性的问题,可以通过大脑信号进行人类交流。虽然想象中的言语可以成为通过大脑信号进行静默通信的范例,但总是很难收集足够的稳定数据来训练解码模式。与此同时,口语数据相对容易获取,这意味着使用口头语言脑信号解码模拟言语的意义。在本文中,我们进行了初步分析,以确定是否可以使用口头语言电子脑谱学数据解码模拟言语,仅仅通过应用经过口头语言脑信号培训的预培训模式来解解码想象中的言语。尽管仅用于培训和验证的言语特征的想象语音数据的分类性能为30.5%,但基于口头语言的叙级数据的转换性能显示的平均准确度为26.8%,与基于语言的言语解码(p = 0.083, chiqare = 4.64 ) 更全面的分析,我们将结果与视觉图像数据集进行比较,这自然与语音表达的言语调相对较少,而仅用于设想性言语的言语学结果。 显示的是,每个视觉图像图像图像图像表现结果之间的明显结果显示为26.0=结果。