Speech data collection at a distance: Comparing the reliability of acoustic cues across homemade recordings

DOI

This dataset contains the supporting data for the presentation at the 179th Meeting of the Acoustical Society of America:Zhang, C., Jepson, K.M., Lohfink, G. & Arvaniti, A. (2020). Speech data collection at a distance: Comparing the reliability of acoustic cues across homemade recordings. The Journal of the Acoustical Society of America, 148 (4). doi: 10.1121/1.5147535It is also related to the following article:Zhang, C., Jepson, K.M., Lohfink, G. & Arvaniti, A. (2021). Comparing acoustic analyses of speech data collected remotely. The Journal of the Acoustical Society of America, 149 (6), 3910-3916. doi: 10.1121/10.0005132Speech production data collection has been significantly impacted by COVID-19 restrictions. Sound-treated recording spaces and high-quality recording devices are inaccessible, and face-to-face interactions are limited. We investigated alternative recording methods that produce data suitable for phonetic analysis, and are accessible to people in their homes. We examined simultaneous recordings of pure tones at seven frequencies (50 Hz, every 100 Hz between 100 Hz and 600 Hz), and three repetitions of the primary cardinal vowels elicited from five trained speakers. Recordings were made using the ZOOM meeting application and non-lossy format smartphone applications (Awesome Voice Recorder, Recorder), comparing these with Zoom H6N reference recordings. F0, F1-4, and duration based on manual segmentation were measured.

Identifier
DOI https://doi.org/10.17026/dans-xk4-kzzr
Metadata Access https://ssh.datastations.nl/oai?verb=GetRecord&metadataPrefix=oai_datacite&identifier=doi:10.17026/dans-xk4-kzzr
Provenance
Creator C. Zhang; K.M. Jepson; G. Lohfink; A. Arvaniti
Publisher DANS Data Station Social Sciences and Humanities
Contributor RU Radboud University
Publication Year 2021
Rights CC BY 4.0; info:eu-repo/semantics/openAccess; http://creativecommons.org/licenses/by/4.0
OpenAccess true
Contact RU Radboud University
Representation
Resource Type Dataset
Format text/xml; text/csv; text/plain; application/zip
Size 5685; 134618; 626; 18865; 5808
Version 1.0
Discipline Acoustics; Agriculture, Forestry, Horticulture, Aquaculture; Agriculture, Forestry, Horticulture, Aquaculture and Veterinary Medicine; Engineering Sciences; Humanities; Life Sciences; Mechanical and industrial Engineering; Mechanics and Constructive Mechanical Engineering; Social Sciences; Social and Behavioural Sciences; Soil Sciences