AUTHOR=Varshney Yash V. , Khan Azizuddin 
  
TITLE=Imagined Speech Classification Using Six Phonetically Distributed Words
  
JOURNAL=Frontiers in Signal Processing
  
VOLUME=Volume 2 - 2022
  
YEAR=2022
  
URL=https://www.frontiersin.org/journals/signal-processing/articles/10.3389/frsip.2022.760643
  
DOI=10.3389/frsip.2022.760643
  
ISSN=2673-8198
  
ABSTRACT=Imagined speech can be used to send commands without any muscle movement or emitting audio. The current status of research is in early stage and there is shortage of open access datasets for imagined speech analysis. In this work, we have proposed an open accessible electroencephalograph (EEG) dataset for six imagined words. We have selected six phonetically distributed, monosyllabic, and emotionally neutral words from W-22 CID word lists. The phonetic distribution of words consisted of the different places of consonants' articulation and different positions of tongue advancement for vowel pronunciation. The selected words were ‘could’, ‘yard’, ‘give’, ‘him’, ‘there’, and ‘toe’. The experiment was performed over 15 subjects who performed the overt and imagined speech task for the displayed word. Each word was presented 50 times in random order. EEG signals were recorded during experiment using 64 channels EEG acquisition system with sampling rate of 2048 Hz.  A preliminary analysis of the recorded data is presented by performing the classification of EEGs corresponding to imagined words. The achieved accuracy is above the chance level for all subjects which suggest the recorded EEGs contain distinctive information about the imagined words.