ArticleJournal of speech, language, and hearing research : JSLHR2023
Reproducible Speech Research With the Artificial Intelligence-Ready PERCEPT Corpora.
Article in Journal of speech, language, and hearing research : JSLHR, 2023. The graph could read no effect estimate from its abstract, so it casts no vote on the map. It is linked to 2 registered trials, which are not on this map. Cited by 5 papers.
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The abstract states no effect estimate the extractor could read, or names no intervention and outcome on the map, so this paper lights no cell and moves no belief. It is still indexed, cited and linked below.
The trial behind it
Trials whose registry record cites this paper, or whose number appears in the abstract. A trial that started after this paper was published is citing it as background, not reporting it.
Visual-acoustic Intervention With Service Delivery In-person and Via Telepractice (VISIT) Non-Inferiority Trial
Randomized Trial of AI-Enhanced Maintenance Training With Visual-Acoustic Biofeedback
Who cites it
5 citing papers in PubMed, 13 citations in OpenAlex.
- CRoP: Context-wise Robust Static Human-Sensing Personalization.Proceedings of the ACM on interactive, mobile, wearable and ubiquitous technologies · 2025Article
- An Introduction to Machine Learning for Speech-Language Pathologists: Concepts, Terminology, and Emerging Applications.Perspectives of the ASHA special interest groups · 2025Article
- Artificial Intelligence-Assisted Speech Therapy for /ɹ/: A Single-Case Experimental Study.American journal of speech-language pathology · 2024Article
- Conducting high-quality and reliable acoustic analysis: A tutorial focused on training research assistants.The Journal of the Acoustical Society of America · 2024Article
- Evaluating acoustic representations and normalization for rhoticity classification in children with speech sound disorders.JASA express letters · 2024Article
Corrections and comments
PubMed lists nothing against this paper. Absence here is not a guarantee, only a check that was made.
Authors and funding
7 authors at 1 institution in 2 countries.
Funding
Abstract
backgroundPublicly available speech corpora facilitate reproducible research by providing open-access data for participants who have consented/assented to data sharing among different research teams. Such corpora can also support clinical education, including perceptual training and training in the use of speech analysis tools. PURPOSE: In this research note, we introduce the PERCEPT (Perceptual Error Rating for the Clinical Evaluation of Phonetic Targets) corpora, PERCEPT-R (Rhotics) and PERCEPT-GFTA (Goldman-Fristoe Test of Articulation), which together contain over 36 hr of speech audio (> 125,000 syllable, word, and phrase utterances) from children, adolescents, and young adults aged 6-24 years with speech sound disorder (primarily residual speech sound disorders impacting /ɹ/) and age-matched peers. We highlight PhonBank as the repository for the corpora and demonstrate use of the associated speech analysis software, Phon, to query PERCEPT-R. A worked example of research with PERCEPT-R, suitable for clinical education and research training, is included as an appendix. Support for end users and information/descriptive statistics for future releases of the PERCEPT corpora can be found in a dedicated Slack channel. Finally, we discuss the potential for PERCEPT corpora to support the training of artificial intelligence clinical speech technology appropriate for use with children with speech sound disorders, the development of which has historically been constrained by the limited representation of either children or individuals with speech impairments in publicly available training corpora.
conclusionsWe demonstrate the use of PERCEPT corpora, PhonBank, and Phon for clinical training and research questions appropriate to child citation speech. Increased use of these tools has the potential to enhance reproducibility in the study of speech development and disorders.
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Registered trials
Read under generation 80e0d062 · epoch 390. Bibliography from PubMed, PubMed Central and OpenAlex; grants from NIH RePORTER; trial links from ClinicalTrials.gov; estimates, votes and beliefs from the OpenQuestion graph.