Assessing objective characterizations of phonetic convergence

This paper focuses on the study of the convergence between characteristics of speech segments– i.e. spectral characteristics of speech sounds – during live interactions between speaking dyads. The interaction data has been collected using an original verbal game called ‘verbal dominoes’ that provides a dense sampling of the acoustic spaces of the interlocutors. Two methods for characterizing phonetic convergence are here compared. The first one is based on a fine-grained analysis of the spectra of central frames of vowels (LDA) while the second one uses a more global speaker recognition technique (LLR). We show that convergence rates calculated by the two techniques correlate as the number of dominoes increases and that the LDA method well resists to the decrease of training and test material. We finally comment the impact of several factors on the computed convergence rates, i.e. interlocutors’ familiarity and sex pairs.