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Applying speech technologies to assess verbal memory in patients with serious mental illness
Verbal memory deficits are some of the most profound neurocognitive deficits associated with schizophrenia and serious mental illness in general. As yet, their measurement in clinical settings is limited to traditional tests that allow for limited administrations and require substantial resources to...
Autores principales: | , , , , , , , |
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Formato: | Online Artículo Texto |
Lenguaje: | English |
Publicado: |
Nature Publishing Group UK
2020
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Materias: | |
Acceso en línea: | https://www.ncbi.nlm.nih.gov/pmc/articles/PMC7066153/ https://www.ncbi.nlm.nih.gov/pubmed/32195368 http://dx.doi.org/10.1038/s41746-020-0241-7 |
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author | Holmlund, Terje B. Chandler, Chelsea Foltz, Peter W. Cohen, Alex S. Cheng, Jian Bernstein, Jared C. Rosenfeld, Elizabeth P. Elvevåg, Brita |
author_facet | Holmlund, Terje B. Chandler, Chelsea Foltz, Peter W. Cohen, Alex S. Cheng, Jian Bernstein, Jared C. Rosenfeld, Elizabeth P. Elvevåg, Brita |
author_sort | Holmlund, Terje B. |
collection | PubMed |
description | Verbal memory deficits are some of the most profound neurocognitive deficits associated with schizophrenia and serious mental illness in general. As yet, their measurement in clinical settings is limited to traditional tests that allow for limited administrations and require substantial resources to deploy and score. Therefore, we developed a digital ambulatory verbal memory test with automated scoring, and repeated self-administration via smart devices. One hundred and four adults participated, comprising 25 patients with serious mental illness and 79 healthy volunteers. The study design was successful with high quality speech recordings produced to 92% of prompts (Patients: 86%, Healthy: 96%). The story recalls were both transcribed and scored by humans, and scores generated using natural language processing on transcriptions were comparable to human ratings (R = 0.83, within the range of human-to-human correlations of R = 0.73–0.89). A fully automated approach that scored transcripts generated by automatic speech recognition produced comparable and accurate scores (R = 0.82), with very high correlation to scores derived from human transcripts (R = 0.99). This study demonstrates the viability of leveraging speech technologies to facilitate the frequent assessment of verbal memory for clinical monitoring purposes in psychiatry. |
format | Online Article Text |
id | pubmed-7066153 |
institution | National Center for Biotechnology Information |
language | English |
publishDate | 2020 |
publisher | Nature Publishing Group UK |
record_format | MEDLINE/PubMed |
spelling | pubmed-70661532020-03-19 Applying speech technologies to assess verbal memory in patients with serious mental illness Holmlund, Terje B. Chandler, Chelsea Foltz, Peter W. Cohen, Alex S. Cheng, Jian Bernstein, Jared C. Rosenfeld, Elizabeth P. Elvevåg, Brita NPJ Digit Med Article Verbal memory deficits are some of the most profound neurocognitive deficits associated with schizophrenia and serious mental illness in general. As yet, their measurement in clinical settings is limited to traditional tests that allow for limited administrations and require substantial resources to deploy and score. Therefore, we developed a digital ambulatory verbal memory test with automated scoring, and repeated self-administration via smart devices. One hundred and four adults participated, comprising 25 patients with serious mental illness and 79 healthy volunteers. The study design was successful with high quality speech recordings produced to 92% of prompts (Patients: 86%, Healthy: 96%). The story recalls were both transcribed and scored by humans, and scores generated using natural language processing on transcriptions were comparable to human ratings (R = 0.83, within the range of human-to-human correlations of R = 0.73–0.89). A fully automated approach that scored transcripts generated by automatic speech recognition produced comparable and accurate scores (R = 0.82), with very high correlation to scores derived from human transcripts (R = 0.99). This study demonstrates the viability of leveraging speech technologies to facilitate the frequent assessment of verbal memory for clinical monitoring purposes in psychiatry. Nature Publishing Group UK 2020-03-11 /pmc/articles/PMC7066153/ /pubmed/32195368 http://dx.doi.org/10.1038/s41746-020-0241-7 Text en © The Author(s) 2020 Open Access This article is licensed under a Creative Commons Attribution 4.0 International License, which permits use, sharing, adaptation, distribution and reproduction in any medium or format, as long as you give appropriate credit to the original author(s) and the source, provide a link to the Creative Commons license, and indicate if changes were made. The images or other third party material in this article are included in the article’s Creative Commons license, unless indicated otherwise in a credit line to the material. If material is not included in the article’s Creative Commons license and your intended use is not permitted by statutory regulation or exceeds the permitted use, you will need to obtain permission directly from the copyright holder. To view a copy of this license, visit http://creativecommons.org/licenses/by/4.0/. |
spellingShingle | Article Holmlund, Terje B. Chandler, Chelsea Foltz, Peter W. Cohen, Alex S. Cheng, Jian Bernstein, Jared C. Rosenfeld, Elizabeth P. Elvevåg, Brita Applying speech technologies to assess verbal memory in patients with serious mental illness |
title | Applying speech technologies to assess verbal memory in patients with serious mental illness |
title_full | Applying speech technologies to assess verbal memory in patients with serious mental illness |
title_fullStr | Applying speech technologies to assess verbal memory in patients with serious mental illness |
title_full_unstemmed | Applying speech technologies to assess verbal memory in patients with serious mental illness |
title_short | Applying speech technologies to assess verbal memory in patients with serious mental illness |
title_sort | applying speech technologies to assess verbal memory in patients with serious mental illness |
topic | Article |
url | https://www.ncbi.nlm.nih.gov/pmc/articles/PMC7066153/ https://www.ncbi.nlm.nih.gov/pubmed/32195368 http://dx.doi.org/10.1038/s41746-020-0241-7 |
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