BELMASK—An Audiovisual Dataset of Adversely Produced Speech for Auditory Cognition Research

Abstract

In this article, we introduce the Berlin Dataset of Lombard and Masked Speech (BELMASK), a phonetically controlled audiovisual dataset of speech produced in adverse speaking conditions, and describe the development of the related speech task. The dataset contains in total 128 min of audio and video recordings of 10 German native speakers (4 female, 6 male) with a mean age of 30.2 years (SD: 6.3 years), uttering matrix sentences in cued, uninstructed speech in four conditions: (i) with a Filtering Facepiece P2 (FFP2) mask in silence, (ii) without an FFP2 mask in silence, (iii) with an FFP2 mask while exposed to noise, (iv) without an FFP2 mask while exposed to noise. Noise consisted of mixed-gender six-talker babble played over headphones to the speakers, triggering the Lombard effect. All conditions are readily available in face-and-voice and voice-only formats. The speech material is annotated, employing a multi-layer architecture, and was originally conceptualized to be used for the administration of a working memory task. The dataset is stored in a restricted-access Zenodo repository and is available for academic research in the area of speech communication, acoustics, psychology and related disciplines upon request, after signing an End User License Agreement (EULA).

Keywords

• face masks
• COVID-19
• German
• matrix sentence test
• face-masked speech
• Lombard speech