Comparing acoustic analyses of speech data collected remotely

DOI

This dataset contains the supporting data for 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: https://doi.org/10.1121/10.0005132Face-to-face speech data collection has been next to impossible globally as a result of the COVID-19 restrictions. To address this problem, simultaneous recordings of three repetitions of the cardinal vowels were made using a Zoom H6 Handy Recorder with an external microphone (henceforth, H6) and compared with two alternatives accessible to potential participants at home: the Zoom meeting application (henceforth, Zoom) and two lossless mobile phone applications (Awesome Voice Recorder, and Recorder; henceforth, Phone). F0 was tracked accurately by all of the devices; however, for formant analysis (F1, F2, F3), Phone performed better than Zoom, i.e., more similarly to H6, although the data extraction method (VoiceSauce, Praat) also resulted in differences. In addition, Zoom recordings exhibited unexpected drops in intensity. The results suggest that lossless format phone recordings present a viable option for at least some phonetic studies.This dataset contains two data files:- "data_Praat.csv" contains data extracted using Praat- "data_VoiceSauce.csv" contains data extracted using VoiceSauceThe full information of participants, materials, recording procedures, and measurements are recorded in the above-mentioned article.

Identifier
DOI https://doi.org/10.17026/dans-zy5-392x
Metadata Access https://phys-techsciences.datastations.nl/oai?verb=GetRecord&metadataPrefix=oai_datacite&identifier=doi:10.17026/dans-zy5-392x
Provenance
Creator C. Zhang; K.M. Jepson; G. Lohfink; A. Arvaniti
Publisher DANS Data Station Phys-Tech Sciences
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 5709; 96313; 782; 96192; 19548; 6427
Version 1.0
Discipline Acoustics; Agriculture, Forestry, Horticulture, Aquaculture; Agriculture, Forestry, Horticulture, Aquaculture and Veterinary Medicine; Construction Engineering and Architecture; Engineering; Engineering Sciences; Humanities; Life Sciences; Mechanical and industrial Engineering; Mechanics and Constructive Mechanical Engineering; Medicine; Social Sciences; Social and Behavioural Sciences; Soil Sciences