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Dynamic Norming and Open Science.

Brian MacWhinney1, Nan Bernstein Ratner2

  • 1Department of Psychology, Carnegie Mellon University, Pittsburgh, PA.

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Researchers highlight the need for open science in speech and hearing research. Freely available tools and data, like those from TalkBank, are crucial for advancing language sample analysis.

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Area of Science:

  • Speech and Hearing Sciences
  • Computational Linguistics
  • Open Science Practices

Background:

  • A recent study proposed a method for assigning Spontaneous Expressive Language (SEM) scores.
  • The method relies on non-public data and proprietary software, limiting reproducibility.
  • This contrasts with open science principles essential for scientific advancement.

Discussion:

  • The current approach by Tucci et al. (2022) lacks transparency due to inaccessible data and non-open-source software.
  • This hinders the validation and broader application of their SEM scoring method.
  • Open science promotes collaboration, verification, and faster progress in research.

Key Insights:

  • TalkBank and the Child Language Data Exchange System offer open-source software and publicly available data.
  • These resources facilitate language sample analysis in line with Open Science standards.
  • Adoption of open science benefits the speech and hearing fields significantly.

Outlook:

  • Promoting open science is vital for the future of speech and hearing research.
  • Wider adoption of open data and software will enhance the reliability and accessibility of language analysis tools.
  • Future research should prioritize transparency and reproducibility.