Reproducible Speech Research with the Artificial-Intelligence-Ready PERCEPT Corpora

Autor: Nina R Benway, Jonathan Preston, Elaine Hitchcock, Yvan Rose, Asif Salekin, Wendy Liang, Tara McAllister
Rok vydání: 2023
Popis: Background: Publicly-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-R and PERCEPT-GFTA corpora, which together contain over 36 hours of speech audio (> 125,000 syllable, word, and phrase utterances) from children, adolescents, and young adults aged 6-24 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 the corpus. 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 Corpus 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. Conclusion: We demonstrate the use of PERCEPT corpora, PhonBank, and Phon for clinical training and research questions appropriate to child citation speech. Increased use these tools has the potential to enhance reproducibility in the study of speech development and disorders.
Databáze: OpenAIRE