IIST BCI Dataset-10 for Telugu Vowels and Consonants

Brain-Computer Interface (BCI) technology makes possible a direct interface between the brain and external devices through the interpretation of neural signals. It is essential to have patient's native language-containing datasets when designing BCI-based solutions for neurological disorders. Current BCI research, though, lacks language-specific datasets, notably for languages like Telugu, which has over 90 million speakers in India. We developed an Electroencephalograph (EEG)-based Brain-Computer Interface (BCI) dataset consisting of EEG signal samples for Telugu Vowels and Consonants. The dataset was collected using the OpenBCI Cyton device that captured EEG data from three Telugu native speakers. The dataset is divided into four sections.1. Vocalized Telugu Vowels and Consonants.2. Subvocalization of Telugu Vowels and Consonants.The Telugu Vowels and Consonants dataset, which was recorded for twenty trials for three volunteer speakers. Based on this dataset, a BCI system to convert EEG signals into both subvocal and vocal forms can be developed to support Telugu language by training this dataset with Machine Learning (ML) and Deep Learning (DL) methods.