  The conversion of brain activity into text using electroencephalography (EEG)
has gained significant traction in recent years. Many researchers are working
to develop new models to decode EEG signals into text form. Although this area
has shown promising developments, it still faces numerous challenges that
necessitate further improvement. It's important to outline this area's recent
developments and future research directions. In this review article, we
thoroughly summarize the progress in EEG-to-text conversion. Firstly, we talk
about how EEG-to-text technology has grown and what problems we still face.
Secondly, we discuss existing techniques used in this field. This includes
methods for collecting EEG data, the steps to process these signals, and the
development of systems capable of translating these signals into coherent text.
We conclude with potential future research directions, emphasizing the need for
enhanced accuracy, reduced system constraints, and the exploration of novel
applications across varied sectors. By addressing these aspects, this review
aims to contribute to developing more accessible and effective Brain-Computer
Interface (BCI) technology for a broader user base.
