Talk2Me: Automated linguistic data collection for personal assessment.

Autor: Majid Komeili, Chloé Pou-Prom, Daniyal Liaqat, Kathleen C Fraser, Maria Yancheva, Frank Rudzicz
Jazyk: angličtina
Rok vydání: 2019
Předmět:
Zdroj: PLoS ONE, Vol 14, Iss 3, p e0212342 (2019)
Druh dokumentu: article
ISSN: 1932-6203
DOI: 10.1371/journal.pone.0212342
Popis: Language is one the earliest capacities affected by cognitive change. To monitor that change longitudinally, we have developed a web portal for remote linguistic data acquisition, called Talk2Me, consisting of a variety of tasks. In order to facilitate research in different aspects of language, we provide baselines including the relations between different scoring functions within and across tasks. These data can be used to augment studies that require a normative model; for example, we provide baseline classification results in identifying dementia. These data are released publicly along with a comprehensive open-source package for extracting approximately two thousand lexico-syntactic, acoustic, and semantic features. This package can be applied arbitrarily to studies that include linguistic data. To our knowledge, this is the most comprehensive publicly available software for extracting linguistic features. The software includes scoring functions for different tasks.
Databáze: Directory of Open Access Journals
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