Speak: A Toolkit Using Amazon Mechanical Turk to Collect and Validate Speech Audio Recordings

Christopher Song, David Harwath, Tuka Alhanai, James Glass


Abstract
We present Speak, a toolkit that allows researchers to crowdsource speech audio recordings using Amazon Mechanical Turk (MTurk). Speak allows MTurk workers to submit speech recordings in response to a task prompt and stimulus (e.g. image, text excerpt, audio file) defined by researchers, a functionality that is not natively offered by MTurk at the time of writing this paper. Importantly, the toolkit employs numerous measures to ensure that speech recordings collected are of adequate quality, in order to avoid accepting unusable data and prevent abuse/fraud. Speak has demonstrated utility, having collected over 600,000 recordings to date. The toolkit is open-source and available for download.
Anthology ID:
2022.lrec-1.787
Volume:
Proceedings of the Thirteenth Language Resources and Evaluation Conference
Month:
June
Year:
2022
Address:
Marseille, France
Venue:
LREC
SIG:
Publisher:
European Language Resources Association
Note:
Pages:
7253–7258
Language:
URL:
https://aclanthology.org/2022.lrec-1.787
DOI:
Bibkey:
Cite (ACL):
Christopher Song, David Harwath, Tuka Alhanai, and James Glass. 2022. Speak: A Toolkit Using Amazon Mechanical Turk to Collect and Validate Speech Audio Recordings. In Proceedings of the Thirteenth Language Resources and Evaluation Conference, pages 7253–7258, Marseille, France. European Language Resources Association.
Cite (Informal):
Speak: A Toolkit Using Amazon Mechanical Turk to Collect and Validate Speech Audio Recordings (Song et al., LREC 2022)
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PDF:
https://preview.aclanthology.org/remove-xml-comments/2022.lrec-1.787.pdf