Accuracy of Automatic Processing of Speech-Language Pathologist and Child Talk During School-Based Therapy Sessions.
Purpose: This study examines the accuracy of Interaction Detection in Early Childhood Settings (IDEAS), a program that automatically transcribes audio files and estimates linguistic units relevant to speech-language therapy, including part-of-speech units that represent features of language complexi...
| Published in: | Journal of Speech, Language & Hearing Research Vol. 67; no. 8; pp. 2669 - 2685 |
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| Main Authors: | , , , , |
| Format: | Article |
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American Speech-Language-Hearing Association
Aug2024
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| Online Access: | View this record in EBSCOhost |
| fields | @attributes: recordID: 1 pdfLink: plink: https://search.ebscohost.com/login.aspx?direct=true&db=ssf&AN=178847313&site=ehost-live header: @attributes: shortDbName: ssf uiTerm: 178847313 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: Aug2024 vid: 67 iid: 8 pid: 42 pub: American Speech-Language-Hearing Association artinfo: ui: 178847313 10.1044/2024_JSLHR-23-00310 ppf: 2669 ppct: 16 formats: fmt: @attributes: type: P size: 941KB tig: atl: Accuracy of Automatic Processing of Speech-Language Pathologist and Child Talk During School-Based Therapy Sessions. aug: au: Johana Chaparro-Moreno, Leydi Gonzalez Villasanti, Hugo Justice, Laura M. Jing Sun Schmitt, Mary Beth affil: Center on the Ecology of Early Development, Boston University, MA Department of Mechanical Engineering, University of Michigan, Ann Arbor Crane Center for Early Childhood Research and Policy, The Ohio State University, Columbus Department of Speech, Language, and Hearing Sciences, Moody College of Communication, The University of Texas at Austin su: Conversation Sound recordings Linguistics School children Patient-professional relations School health services Language acquisition Treatment of language disorders Automatic speech recognition Research funding Natural language processing Descriptive statistics Speech therapy Video recording sug: subj: Conversation Sound recordings Linguistics School children Patient-professional relations School health services Language acquisition Integrated Record Production/Distribution Sound recording merchant wholesalers Record Production Treatment of language disorders Automatic speech recognition Research funding Natural language processing Descriptive statistics Speech therapy Video recording ab: Purpose: This study examines the accuracy of Interaction Detection in Early Childhood Settings (IDEAS), a program that automatically transcribes audio files and estimates linguistic units relevant to speech-language therapy, including part-of-speech units that represent features of language complexity, such as adjectives and coordinating conjunctions. Method: Forty-five video-recorded speech-language therapy sessions involving 27 speech-language pathologists (SLPs) and 56 children were used. The F measure determines the accuracy of IDEAS diarization (i.e., speech segmentation and speaker classification). Two additional evaluation metrics, namely, median absolute relative error and correlation, indicate the accuracy of IDEAS for the estimation of linguistic units as compared with two conditions, namely, Oracle (manual diarization) and Voice Type Classifier (existing diarizer with acceptable accuracy). Results: The high F measure for SLP talk data suggests high accuracy of IDEAS diarization for SLP talk but less so for child talk. These differences are reflected in the accuracy of IDEAS linguistic unit estimates. IDEAS median absolute relative error and correlation values for nine of the 10 SLP linguistic unit estimates meet the accuracy criteria, but none of the child linguistic unit estimates meet these criteria. The type of linguistic units also affects IDEAS accuracy. Conclusions: IDEAS was tailored to educational settings to automatically convert audio recordings into text and to provide linguistic unit estimates in speechlanguage therapy sessions and classroom settings. Although not perfect, IDEAS is reliable in automatically capturing and returning linguistic units, especially in SLP talk, that are relevant in research and practice. The tool offers a way to automatically measure SLP talk in clinical settings, which will support research seeking to understand how SLP talk influences children's language growth. pubtype: Academic Journal doctype: Article src: R language: English refInfo: copyright: @attributes: flag: N holdings: @attributes: islocal: N |
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