2022/07/12 by Andreas Liesenfeld, Mark Dingemanse · 1 voice
Computer Science · Arts and Humanities · #Speech and dialogue systems #Digital Communication and Language #Language, Discourse, Communication Strategies
paper · pdf · doi:10.31234/osf.io/w8hpy
openalex publication_date 2022/07/12 · openalex created_date 2025/10/10 · openalex updated_date 2026/08/01
Response tokens (also known as backchannels, continuers, or feedback) are a frequent feature of human interaction, where they serve to display understanding and streamline turn-taking. We propose a bottom-up method to study responsive behaviour across 16 languages (8 language families). We use sequential context and recurrence of turns formats to identify candidate response tokens in a language-agnostic way across diverse conversational corpora. We then use UMAP clustering directly on speech signals to represent structure and variation. We find that (i) written orthographic annotations underrepresent the attested variation, (ii) distinctions between formats can be gradient rather than discrete, (iii) most languages appear to make available a broad distinction between a minimal nasal format ‘mm’ and a fuller ‘yeah’-like format. Charting this aspect of human interaction contributes to our understanding of interactional infrastructure across languages and can inform the design of speech technologies.