MotherBoard’s Mother Tongue is a computational linguistics and artistic research project that explores a Large Language Model’s (LLM) vocal production of glossolalia. Glossolalia, colloquially known as ‘speaking in tongues,’ consists of the human production of seemingly unintelligible utterances. It is, by its nature, difficult to annotate accurately with linguistic features relevant for natural language. The glossolalia-producing system demonstrated here consists of the interaction of 1) a ‘nonsense’ linguistic corpus 2) a micro-controller based environmental data stream and 3) a fine-tuned LLM. While discussing some philosophical and artistic considerations of machinic glossolalia, we also address some methodological considerations for Natural Language Processing (NLP). Using the artistic project as a case study, we argue that machinic glossolalia presents a ‘stress test’ that could inform both creative redirections of NLP methods and the definitions held by the subfield.