ABSTRACT
This chapter begins with a brief review of early efforts to automatically assess pronunciation, which generally focused on constrained speech. It discusses the approaches used for measurement of pronunciation in unconstrained language, including an exploration of whether and how measures used for highly predictable speech can be applied to less predictable speech, as well as other approaches such as the use of measures that do not require any knowledge of the words used. The chapter also discusses validity issues related to the automated scoring of pronunciation in unconstrained speech, focusing on how advance considerations of evidence needed to support the various claims in a validity argument can encourage critical thinking about conceptual issues involved in automated pronunciation assessment, as well as principled development of specific approaches to evaluating pronunciation. It concludes with the impact of continuing improvements in speech recognition technology and improvements to pronunciation measures stimulated by such trends as the rise of "Big Data".
