论文标题
使用脑电图信号解码语言特定想象的语音的神经相关性
Decoding Neural Correlation of Language-Specific Imagined Speech using EEG Signals
论文作者
论文摘要
由于脑病变和退化性疾病而导致的语音障碍可能是毁灭性的。对于具有严重语音缺陷的人来说,脑部计算机界面中想象中的言语是重建语音产生的神经信号的希望。然而,由于空间和时间信息的差异很高以及信噪比较低,因此基于EEG的想象语音域的研究仍然存在一些局限性。在本文中,我们调查了两组以不同语言(英语和中文)的任务的母语人士的神经信号。我们的假设是,与中文,基于音调和意识形态图的语言相比,英语是一种非色调和基于唱片的语言,在神经计算方面的频谱差异。结果表明,在特定的频带组中,英语和中文之间的相对功率谱密度有显着差异。同样,在想象力的任务中,对theta频段中汉语中熟人的空间评估也很独特。因此,本文将在解码语音的神经信号时提出单词想象的关键频谱和空间信息。
Speech impairments due to cerebral lesions and degenerative disorders can be devastating. For humans with severe speech deficits, imagined speech in the brain-computer interface has been a promising hope for reconstructing the neural signals of speech production. However, studies in the EEG-based imagined speech domain still have some limitations due to high variability in spatial and temporal information and low signal-to-noise ratio. In this paper, we investigated the neural signals for two groups of native speakers with two tasks with different languages, English and Chinese. Our assumption was that English, a non-tonal and phonogram-based language, would have spectral differences in neural computation compared to Chinese, a tonal and ideogram-based language. The results showed the significant difference in the relative power spectral density between English and Chinese in specific frequency band groups. Also, the spatial evaluation of Chinese native speakers in the theta band was distinctive during the imagination task. Hence, this paper would suggest the key spectral and spatial information of word imagination with specialized language while decoding the neural signals of speech.