Linguistic analysis of human-computer interaction

Abstract

This article reviews recent literature investigating speech variation in production and comprehension during spoken language communication between humans and devices. Human speech patterns toward voice-AI presents a test to our scientific understanding about speech communication and language use. First, work exploring how human-AI interactions are similar to, or different from, human-human interactions in the realm of speech variation is reviewed. In particular, we focus on studies examining how users adapt their speech when resolving linguistic misunderstandings by computers and when accommodating their speech toward devices. Next, we consider work that investigates how top-down factors in the interaction can influence users’ linguistic interpretations of speech produced by technological agents and how the ways in which speech is generated (via text-to-speech synthesis, TTS) and recognized (using automatic speech recognition technology, ASR) has an effect on communication. Throughout this review, we aim to bridge both HCI frameworks and theoretical linguistic models accounting for variation in human speech. We also highlight findings in this growing area that can provide insight to the cognitive and social representations underlying linguistic communication more broadly. Additionally, we touch on the implications of this line of work for addressing major societal issues in speech technology.