Automation of Language Sample Analysis.
Purpose: A major barrier to the wider use of language sample analysis (LSA) is the fact that transcription is very time intensive. Methods that can reduce the required time and effort could help in promoting the use of LSA for clinical prac- tice and research. Method: This article describes an autom...
| Publicado en: | Journal of Speech, Language & Hearing Research Vol. 66; no. 7; pp. 2421 - 2434 |
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| Autores principales: | , , , |
| Formato: | Artículo |
| Publicado: |
American Speech-Language-Hearing Association
Jul2023
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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=164881408&site=ehost-live header: @attributes: shortDbName: ssf uiTerm: 164881408 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: Jul2023 vid: 66 iid: 7 pid: 42 pub: American Speech-Language-Hearing Association artinfo: ui: 164881408 10.1044/2023_JSLHR-22-00642 ppf: 2421 ppct: 13 formats: fmt: @attributes: type: P size: 705KB tig: atl: Automation of Language Sample Analysis. aug: au: Houjun Liu MacWhinney, Brian Fromm, Davida Lanzi, Alyssa affil: The Nueva School, San Mateo, CA. Department of Psychology, Carnegie Mellon University, Pittsburgh, PA. Communication Sciences and Disorders Department, University of Delaware, Newark. su: Computer software Speech therapy Phonological awareness Speech evaluation Automatic speech recognition Acquisition of data Articulation disorders Automation sug: subj: Computer, computer peripheral and pre-packaged software merchant wholesalers Computer and Computer Peripheral Equipment and Software Merchant Wholesalers Computer and software stores Software publishers (except video game publishers) Computer software Speech therapy Phonological awareness Speech evaluation Automatic speech recognition Acquisition of data Articulation disorders Automation ab: Purpose: A major barrier to the wider use of language sample analysis (LSA) is the fact that transcription is very time intensive. Methods that can reduce the required time and effort could help in promoting the use of LSA for clinical prac- tice and research. Method: This article describes an automated pipeline, called Batchalign, that takes raw audio and creates full transcripts in Codes for the Human Analysis of Talk (CHAT) transcription format, complete with utterance- and word-level time alignments and morphosyntactic analysis. The pipeline only requires major human intervention for final checking. It combines a series of existing tools with additional novel reformatting processes. The steps in the pipeline are (a) auto- matic speech recognition, (b) utterance tokenization, (c) automatic corrections, (d) speaker ID assignment, (e) forced alignment, (f) user adjustments, and (g) automatic morphosyntactic and profiling analyses. Results: For work with recordings from adults with language disorders, six major results were obtained: (a) The word error rate was between 2.4% for con- trols and 3.4% for patients, (b) utterance tokenization accuracy was at the level reported for speakers without language disorders, (c) word-level diarization accuracy was at 93% for control participants and 83% for participants with lan- guage disorders, (d) utterance-level diarization accuracy based on word-level diarization was high, (e) adherence to CHAT format was fully accurate, and (f) human transcriber time was reduced by up to 75%. Conclusion: The pipeline dramatically shortens the time gap between data col- lection and data analysis and provides an output superior to that typically gen- erated by human transcribers. pubtype: Academic Journal doctype: Article src: R language: English refInfo: copyright: @attributes: flag: N holdings: @attributes: islocal: N |
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