Introduction to the special issue emergence of speech and language from prediction error: error-driven language models

Abstract

Last year, 2022, marked the 50th anniversary of the Rescorla-Wagner learning equations–a landmark in the development of learning theory. Originally based on animal learning, the equations and error-driven learning models as a whole were rapidly adopted and applied in several areas of human psychology. While language acquisition research initially took a different path, interest in the role of error-driven learning in language is growing. With the aim of strengthening this emerging research field, sparking discussion and cross-fertilisation of ideas across linguistics, psychology and cognate fields, this Special Issue presents nine papers that address the role of error-driven learning in language. The papers investigate a wide range of subfields of linguistics, and include two review articles, in addition to computational modelling and experimental research. The collection thus serves both as an introduction for those new to the subject and as an overview for those already working in the field.