Evidence map›Paper›PMID 42418715›Full record

ArticleJMIR research protocols2026

My Voice Library: Protocol for Developing Audio and Visual Datasets to Enable Personalized Real-Time Communication for People With Dysarthria.

Petra Karlsson, Andrea Bandini, Michelle McInerney, Hayley Smithers-Sheedy, Annemarie Murphy, Maria Dalmon, Alistair McEwan, Silvia Orlandi

Abstract read
In one paragraph

Article in JMIR research protocols, 2026. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Not yet cited in PubMed.

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0cells of the map it votes in
0citing papers in PubMed
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1 · What the graph read from it

What it found

Each row is one number read from the abstract, on the scale the paper reported it, with its interval. Left of the dashed line favours the treatment, right favours the comparator. Under each row is the sentence it came from. New to these charts? A ten-minute tutorial.

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.

2 · The registry

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.

Neither the registry nor the abstract names a trial number. If this is a trial report, that itself is worth knowing.

3 · Its place in the literature

Who cites it

0 citing papers in PubMed.

No citing paper in PubMed yet.

4 · The record

Corrections and comments

PubMed lists nothing against this paper. Absence here is not a guarantee, only a check that was made.

5 · Who and what money

Authors and funding

8 authors.

Petra KarlssonFaculty of Medicine and Health, Cerebral Palsy Alliance, The University of Sydney, 88 Mallett Street, Camperdown, NB, 2050, Australia, 61 0447508661.ORCID 0000-0002-6253-9488
Andrea BandiniThe Biorobotics Institute & the Department of Excellence for Robotics and AI, Scuola Superiore Sant'Anna, Pisa, Italy.ORCID 0000-0002-3509-2887
Michelle McInerneyDepartment of Language & Cognition, Faculty of Brain Sciences, University College London (UCL), London, United Kingdom.ORCID 0000-0002-9713-6566
Hayley Smithers-SheedyFaculty of Medicine and Health, Cerebral Palsy Alliance, The University of Sydney, 88 Mallett Street, Camperdown, NB, 2050, Australia, 61 0447508661.ORCID 0000-0002-7888-872X
Annemarie MurphyFaculty of Medicine and Health, Cerebral Palsy Alliance, The University of Sydney, 88 Mallett Street, Camperdown, NB, 2050, Australia, 61 0447508661.ORCID 0000-0001-5147-2487
Maria DalmonCerebral Palsy Alliance, Allambie Heights, New South Wales, Australia.
Alistair McEwanCerebral Palsy Alliance, Allambie Heights, New South Wales, Australia.ORCID 0000-0001-7597-6372
Silvia OrlandiDepartment of Electrical, Electronic, and Information Engineering "Guglielmo Marconi" - DEI, University of Bologna, Bologna, Italy.ORCID 0000-0003-2733-8450

Funding

National Health and Medical Research Council 201288220,12,882
6 · The paper itself

Abstract

Background: Communication is a human right; despite this, children with cerebral palsy and dysarthria experience constraints due to their physical disability, affecting their opportunity to reach their full potential and ability to fully participate in play, school, and socializing. For many, their challenge to produce clear speech that can be understood is interpreted by others as an intellectual impairment. Children with moderate-severe speech impairments such as dysarthria often rely on technology solutions, which can translate text or symbols to speech manually or using a single binary switch, scanning hierarchical switch‑access menus. This is time-consuming, arduous, and 15 to 20 times slower than normal speech. Technology innovations, developed via high-quality datasets of audio-video samples of dysarthric speech, hold the key to build personalized speech-recognition algorithms that allow us to bridge this gap. Objective: My Voice Library is a repository of high-quality audio and visual datasets of children living in Australia with cerebral palsy who have dysarthria. The children are presented with gamified modules based on words and sentences from the Frenchay Dysarthria Assessment 2 to allow speech and language therapists, engineers. and programmers to develop personalized speech-recognition approaches to enable personalized real-time communication. Methods: Our ethics and consenting process enables participants (8-18 y) to choose if they want their information to be used for personalized research in addition to general research. The study has been approved by the University of Sydney's Human Research Ethics Committee (2023/263). Caregivers of the participants provide written informed consent. The results will be disseminated through contributions to international conferences and scientific journals, and they will also be included in students' theses. Results: The National Health and Medical Research Council funded the study in April 2021. Data collection commenced in March 2024 and will continue until 99 participants have been recruited, after which the database will remain active. As of April 2026, thirteen of 99 participants have been recruited. Preliminary data analysis commenced in 2026. The results from the preliminary analysis are expected to be published in 2027, with full results to be published once 99 participants have been successfully recruited. Conclusions: My Voice Library embeds high-quality voice and video data assessments through gamified modules based on the Frenchay Dysarthria Assessment 2 and was designed in partnership with an active patient and a public involvement advisory group. My Voice Library and its associated information governance will facilitate the research use of real-world data where ethical approval and consent are given. My Voice Library enables the collection of voice data in controlled yet naturalistic environments for children, enhancing the clinical relevance and quality of the dataset. The modular and gamified design promotes sustained participant engagement, reduces fatigue, and increases the quantity and diversity of data collected.

Indexed as

DysarthriaAustraliaCerebral PalsyChildHumanscerebral palsycommunicationpatient and public involvementspeech impairmenttechnology

Identifiers

PMID42418715
PMCPMC13345347

What OpenQuestion holds

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LicenceCC BY
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Registered trials

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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.