Imagined speech (also called silent speech, covert speech, inner speech, or, in the original Latin terminology used by clinicians, endophasia) is thinking in the form of sound – “hearing” one’s own voice silently to oneself, without the intentional movement of any extremities such as the lips, tongue, or hands. Logically, imagined speech has been possible since the emergence of language, however, the phenomenon is most associated with its investigation through signal processing and detection within electroencephalograph (EEG) data as well as data obtained using alternative non-invasive, brain–computer interface (BCI) devices. History In 2008, the US Defense Advanced Research Projects Agency (DARPA) provided a $4 million grant to the University of California (Irvine), with the intent of providing a foundation for synthetic telepathy. According to DARPA, the project “will allow user-to-user communication on the battlefield without the use of vocalized speech through neural signals analysis. The brain generates word-specific signals prior to sending electrical impulses to the vocal cords. These imagined speech signals would be analyzed and translated into distinct words allowing covert person-to-person communication.” In his "Impossible languages" (2016) Andrea Moro discusses the "sound of thoughts" and the relationship between linguistics units and imagined speech, mainly capitalizing on Magrassi et al. (2015) "Sound representation in higher language areas during language production". DARPA's program outline has three major goals: To attempt to identify EEG patterns unique to individual words To ensure these patterns are common to different users to avoid extensive device training To construct a prototype that would decode the signals and transmit them over a limited range Detection methods The process for analyzing subjects' silent speech is composed of recording subjects’ brain waves, and then using a computer to process the data and determine the content of the subjects' covert speech. Recording Subject neural patterns (brain waves) can be recorded using BCI devices; currently, use of non-invasive devices, specifically the EEG, is of greater interest to researchers than invasive and partially invasive types. This is because non-invasive types pose the least risk to subject health; EEG's have attracted the greatest interest because they offer the most user-friendly approach in addition to having far less complex instrumentation than that of functional magnetic resonance imaging (fMRI’s), another commonly used non-invasive BCI. Processing The first step in processing non-invasive data is to remove artifacts such as eye movement and blinking, as well as other electromyographic activity. After artifact-removal, a series of algorithms