The Harvard/IEEE (henceforth H/I) sentences are widely used for testing speech recognition in English. This study examined whether two talker characteristics, race and gender, are conveyed by 80 of the H/I sentences in their written form, and by a comparison set of sentences from the internet message board Reddit, which were expected to convey social information. As predicted, a significant proportion of raters reported perceiving race and gender information in the H/I sentences. Suggestions of how to manage the potential influence of this social information on measures of speech intelligibility are provided.
Download full-text PDF |
Source |
|---|---|
| http://www.ncbi.nlm.nih.gov/pmc/articles/PMC8693192 | PMC |
| http://dx.doi.org/10.1121/10.0007466 | DOI Listing |
Publication Analysis
Top Keywords
Similar Publications
A text-based computational framework for patient -specific modeling for classification of cancers.
iScience
March 2022
Institute for Protein Research, Osaka University, Suita, Osaka 565-0871, Japan.
Patient heterogeneity precludes cancer treatment and drug development; hence, development of methods for finding prognostic markers for individual treatment is urgently required. Here, we present Pasmopy (Patient-Specific Modeling in Python), a computational framework for stratification of patients using signaling dynamics. Pasmopy converts texts and sentences on biochemical systems into an executable mathematical model.
View Article and Find Full Text PDFWritten standard sentence materials convey social information.
JASA Express Lett
December 2021
Department of Speech-Language-Hearing Sciences, University of Minnesota-Twin Cities, Minneapolis, Minnesota 55455, USA
The Harvard/IEEE (henceforth H/I) sentences are widely used for testing speech recognition in English. This study examined whether two talker characteristics, race and gender, are conveyed by 80 of the H/I sentences in their written form, and by a comparison set of sentences from the internet message board Reddit, which were expected to convey social information. As predicted, a significant proportion of raters reported perceiving race and gender information in the H/I sentences.
View Article and Find Full Text PDFIdentification of the Somatomotor Network from Language Task-based fMRI Compared with Resting-State fMRI in Patients with Brain Lesions.
Radiology
October 2021
From the Division of Neuroradiology, the Russell H. Morgan Department of Radiology and Radiological Science (E.B., R.J., A.M.S., S.A., J.J.P., S.K.G., H.I.S.) and the Department of Neurosurgery (J.J.P.), Johns Hopkins University School of Medicine, 600 N Wolfe St, Baltimore, MD 21287; Division of Neuroradiology, Department of Radiology, Temple University Hospital, Philadelphia, Pa (V.S.); Department of Biostatistics, Johns Hopkins University Bloomberg School of Public Health, Baltimore, Md (G.W., M.A.L., B.S.C.); and the Malone Center for Engineering in Healthcare, the Whiting School of Engineering, Johns Hopkins University, Baltimore, Md (H.I.S.).
Background Resting-state functional MRI (rs-fMRI) is a potential alternative to task-based functional MRI (tb-fMRI) for somatomotor network (SMN) identification. Brain networks can also be generated from tb-fMRI by using independent component analysis (ICA). Purpose To investigate whether the SMN can be identified by using ICA from a language task without a motor component, the sentence completion functional MRI (sc-fMRI) task, compared with rs-fMRI.
View Article and Find Full Text PDFAuthor Correction: Drug-mediated metabolic tipping between antibiotic resistant states in a mixed-species community.
Nat Ecol Evol
November 2018
Biosciences, University of Exeter, Exeter, UK.
In the version of this Article originally published, the following sentence was missing from the Acknowledgements: "R.E.B.
View Article and Find Full Text PDFAmerican Society of Functional Neuroradiology-Recommended fMRI Paradigm Algorithms for Presurgical Language Assessment.
AJNR Am J Neuroradiol
October 2017
From the Mayo Clinic (D.F.B., K.W.), Rochester Minnesota.
Introduction: Functional MR imaging is increasingly being used for presurgical language assessment in the treatment of patients with brain tumors, epilepsy, vascular malformations, and other conditions. The inherent complexity of fMRI, which includes numerous processing steps and selective analyses, is compounded by institution-unique approaches to patient training, paradigm choice, and an eclectic array of postprocessing options from various vendors. Consequently, institutions perform fMRI in such markedly different manners that data sharing, comparison, and generalization of results are difficult.
View Article and Find Full Text PDFWant AI Summaries of new PubMed Abstracts delivered to your In-box?
Enter search terms and have AI summaries delivered each week - change queries or unsubscribe any time!