Automated Measures of Syntactic Complexity in Natural Speech Production: Older and Younger Adults as a Case Study.
Purpose: Multiple methods have been suggested for quantifying syntactic complexity in speech. We compared eight automated syntactic complexity metrics to determine which best captured verified syntactic differences between old and young adults. Method: We used natural speech samples produced in a pi...
| Publicado en: | Journal of Speech, Language & Hearing Research Vol. 67; no. 2; pp. 545 - 562 |
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| Autores principales: | , , , , , , |
| Formato: | Artículo |
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American Speech-Language-Hearing Association
Feb2024
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| Materias: | |
| Acceso en línea: | Ver este registro en EBSCOhost |
| fields | @attributes: recordID: 1 pdfLink: plink: https://search.ebscohost.com/login.aspx?direct=true&db=ssf&AN=175404828&site=ehost-live header: @attributes: shortDbName: ssf uiTerm: 175404828 longDbName: Social Sciences Full Text (H.W. Wilson) uiTag: AN controlInfo: bkinfo: jinfo: jid: 10924388 1SM jtl: Journal of Speech, Language & Hearing Research issn: 10924388 maglogo: N pubinfo: dt: Feb2024 vid: 67 iid: 2 pid: 42 pub: American Speech-Language-Hearing Association artinfo: ui: 175404828 10.1044/2023_JSLHR-23-00009 ppf: 545 ppct: 17 formats: fmt: @attributes: type: P size: 1.3MB tig: atl: Automated Measures of Syntactic Complexity in Natural Speech Production: Older and Younger Adults as a Case Study. aug: au: Agmon, Galit Pradhan, Sameer Ash, Sharon Nevler, Naomi Liberman, Mark Grossman, Murray Chob, Sunghye affil: Frontotemporal Degeneration Center, Department of Neurology, Perelman School of Medicine, University of Pennsylvania, Philadelphia. Linguistic Data Consortium, University of Pennsylvania, Philadelphia. su: Pennsylvania Age distribution Diffusion of innovations Speech perception Multivariate analysis Speech evaluation Descriptive statistics Research funding Logistic regression analysis sug: subj: Age distribution Diffusion of innovations Pennsylvania Speech perception Multivariate analysis Speech evaluation Descriptive statistics Research funding Logistic regression analysis ab: Purpose: Multiple methods have been suggested for quantifying syntactic complexity in speech. We compared eight automated syntactic complexity metrics to determine which best captured verified syntactic differences between old and young adults. Method: We used natural speech samples produced in a picture description task by younger (n = 76, ages 18-22 years) and older (n = 36, ages 53-89 years) healthy participants, manually transcribed and segmented into sentences. We manually verified that older participants produced fewer complex structures. We developed a metric of syntactic complexity using automatically extracted syntactic structures as features in a multidimensional metric. We compared our metric to seven other metrics: Yngve score, Frazier score, Frazier–Roark score, developmental level, syntactic frequency, mean dependency distance, and sentence length. We examined the success of each metric in identifying the age group using logistic regression models. We repeated the analysis with automatic transcription and segmentation using an automatic speech recognition (ASR) system. Results: Our multidimensional metric was successful in predicting age group (area under the curve [AUC] = 0.87), and it performed better than the other metrics. High AUCs were also achieved by the Yngve score (0.84) and sentence length (0.84). However, in a fully automated pipeline with ASR, the performance of these two metrics dropped (to 0.73 and 0.46, respectively), while the performance of the multidimensional metric remained relatively high (0.81). Conclusions: Syntactic complexity in spontaneous speech can be quantified by directly assessing syntactic structures and considering them in a multivariable manner. It can be derived automatically, saving considerable time and effort compared to manually analyzing large-scale corpora, while maintaining high face validity and robustness. pubtype: Academic Journal doctype: Article src: R language: English refInfo: copyright: @attributes: flag: N holdings: @attributes: islocal: N |
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