Challenges and Methods in Annotating Natural Speech for Neurolinguistic Research Article Swipe
Galit Agmon
,
Manuela Jaeger
,
Ella Magen
,
Danna Pinto
,
Yuval Perelmuter
,
Elana Zion Golumbic
,
Martin G. Bleichner
·
YOU?
·
· 2025
· Open Access
·
· DOI: https://doi.org/10.1162/nol.a.12
YOU?
·
· 2025
· Open Access
·
· DOI: https://doi.org/10.1162/nol.a.12
Spoken language is central to human communication, influencing cognition, learning, and social interactions. Despite its spontaneous nature, characterized by disfluencies, fillers, self-corrections and irregular syntax, it effectively serves its communicative purpose. Understanding how the brain processes natural language offers valuable insights into the neurobiology of language. Recent neuroscience advancements allow us to study neural processes in response to ongoing speech, requiring detailed, time-locked descriptions of speech material to capture the nuances of spoken language. While there are many speech-to-text tools available, obtaining a time-locked true verbatim transcript, reflecting everything that was uttered, requires additional effort to achieve an accurate representation. We demonstrate the challenges involved in the process of obtaining time-resolved annotation of spontaneous speech, by presenting two semi-automatic pipelines, developed for German and Hebrew but adaptable to other languages. The outputs of these pipelines enable analyses of the neural representation and processing of key linguistic features. We discuss the methodological challenges and opportunities posed by current state-of-the-art pipelines, and advocate for new lines of natural language processing research aimed at advancing our understanding of how the brain processes everyday language.
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- Type
- article
- Language
- en
- Landing Page
- https://doi.org/10.1162/nol.a.12
- https://direct.mit.edu/nol/article-pdf/doi/10.1162/nol.a.12/2529049/nol.a.12.pdf
- OA Status
- gold
- References
- 131
- Related Works
- 10
- OpenAlex ID
- https://openalex.org/W4410983472
All OpenAlex metadata
Raw OpenAlex JSON
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https://openalex.org/W4410983472Canonical identifier for this work in OpenAlex
- DOI
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https://doi.org/10.1162/nol.a.12Digital Object Identifier
- Title
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Challenges and Methods in Annotating Natural Speech for Neurolinguistic ResearchWork title
- Type
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articleOpenAlex work type
- Language
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enPrimary language
- Publication year
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2025Year of publication
- Publication date
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2025-01-01Full publication date if available
- Authors
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Galit Agmon, Manuela Jaeger, Ella Magen, Danna Pinto, Yuval Perelmuter, Elana Zion Golumbic, Martin G. BleichnerList of authors in order
- Landing page
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https://doi.org/10.1162/nol.a.12Publisher landing page
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https://direct.mit.edu/nol/article-pdf/doi/10.1162/nol.a.12/2529049/nol.a.12.pdfDirect link to full text PDF
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YesWhether a free full text is available
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goldOpen access status per OpenAlex
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https://direct.mit.edu/nol/article-pdf/doi/10.1162/nol.a.12/2529049/nol.a.12.pdfDirect OA link when available
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Computer science, Syntax, Spoken language, Natural (archaeology), Representation (politics), Natural language, German, Linguistics, Natural language processing, Cognitive science, Psychology, Politics, Philosophy, Law, Archaeology, Political science, HistoryTop concepts (fields/topics) attached by OpenAlex
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0Total citation count in OpenAlex
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10Other works algorithmically related by OpenAlex
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