CoVox: A dataset of contrasting vocalizations.

Abstract

The human voice is remarkably versatile and can vary greatly in sound depending on how it is used. An increasing number of studies have addressed the differences and similarities between the singing and the speaking voice. However, finding adequate stimuli material that is at the same time controlled and ecologically valid is challenging, and most datasets lack variability in terms of vocal styles performed by the same voice. Here, we describe a curated stimulus set of vocalizations where 22 female singers performed the same melody excerpts in three contrasting singing styles (as a lullaby, as a pop song, and as an opera aria) and spoke the text aloud in two speaking styles (as if speaking to an adult or to an infant). All productions were made with the songs' original lyrics, in Brazilian Portuguese, and with a/lu/sound. This ecologically valid dataset of 1320 vocalizations was validated through a forced-choice lab experiment (N = 25 for each stimulus) where lay listeners could recognize the intended vocalization style with high accuracy (proportion of correct recognition superior to 69% for all styles). We also provide acoustic characterization of the stimuli, depicting clear and contrasting acoustic profiles depending on the style of vocalization. All recordings are made freely available under a Creative Commons license and can be downloaded at https://osf.io/cgexn/ .