ArticleJournal of applied statistics2019
Statistical considerations for crowdsourced perceptual ratings of human speech productions.
Article in Journal of applied statistics, 2019. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Cited by 3 papers.
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The abstract states no effect estimate the extractor could read, or names no intervention and outcome on the map, so this paper lights no cell and moves no belief. It is still indexed, cited and linked below.
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Who cites it
3 citing papers in PubMed.
- Does the Use of Crowdsourced Listeners Yield Different Speech Intelligibility Results Than In-Person Listeners for Typically Developing Children?Journal of speech, language, and hearing research : JSLHR · 2026Article
- The Multilevel Word Accuracy Composite Scale: A Novel Measure of Speech Production in Childhood Apraxia of Speech.American journal of speech-language pathology · 2023Article
- Vocal development in a large-scale crosslinguistic corpus.Developmental science · 2021Article
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Authors and funding
4 authors.
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Abstract
Crowdsourcing has become a major tool for scholarly research since its introduction to the academic sphere in 2008. However, unlike in traditional laboratory settings, it is nearly impossible to control the conditions under which workers on crowdsourcing platforms complete tasks. In the study of communication disorders, crowdsourcing has provided a novel solution to the collection of perceptual ratings of human speech production. Such ratings allow researchers to gauge whether a treatment yields meaningful change in how human listeners' perceive disordered speech. This paper will explore some statistical considerations of crowdsourced data with specific focus on collecting perceptual ratings of human speech productions. Random effects models are applied to crowdsourced perceptual ratings collected in both a continuous and binary fashion. A simulation study is conducted to test the reliability of the proposed models under differing numbers of workers and tasks. Finally, this methodology is applied to a data set from the study of communication disorders.
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