Evidence map›Paper›PMID 37346421›Full record

ArticleFrontiers in psychology2023

Talkitt: toward a new instrument based on artificial intelligence for augmentative and alternative communication in children with down syndrome.

Floriana Costanzo, Elisa Fucà, Cristina Caciolo, Deborah Ruà, Sara Smolley, Danny Weissberg, Stefano Vicari

Open access · goldAbstract read
In one paragraph

Article in Frontiers in psychology, 2023. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Cited by 1 paper.

0numbers the graph read from it
0cells of the map it votes in
1citing papers in PubMed
4.6field-weighted citation impact, top 6% of its field
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

1 citing paper in PubMed, 7 citations in OpenAlex.

  1. Article
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

7 authors at 2 institutions in 1 country.

Floriana CostanzoChild and Adolescent Neuropsychiatry Unit, Bambino Gesù Children's Hospital, IRCCS, Rome, Italy.
Elisa FucàChild and Adolescent Neuropsychiatry Unit, Bambino Gesù Children's Hospital, IRCCS, Rome, Italy.
Cristina CacioloChild and Adolescent Neuropsychiatry Unit, Bambino Gesù Children's Hospital, IRCCS, Rome, Italy.
Deborah RuàChild and Adolescent Neuropsychiatry Unit, Bambino Gesù Children's Hospital, IRCCS, Rome, Italy.
Sara SmolleyVoiceitt Ltd., Buffalo, NY, United States.
Danny WeissbergVoiceitt Ltd., Buffalo, NY, United States.
Stefano VicariChild and Adolescent Neuropsychiatry Unit, Bambino Gesù Children's Hospital, IRCCS, Rome, Italy.
Bambino Gesù Children's Hospital · ITUniversità Cattolica del Sacro Cuore · IT

Funding

No grant is acknowledged in the PubMed record.

6 · The paper itself

Abstract

Introduction: Individuals with Down syndrome (DS) often exhibit a severe speech impairment, with important consequences on language intelligibility. For these cases, the use of Augmentative Alternative Communication instruments, that increase an individual's communication abilities, becomes crucial. Talkitt is a mobile application created by Voiceitt Company, exploiting speech recognition technology and artificial intelligence models to translate in real-time unintelligible sounds into clear words, allowing individuals with language production impairment to verbally communicate in real-time. Methods: The study evaluated the usability and satisfaction related to the Talkitt application use, as well as effects on adapted behavior and communication, of participants with DS. A final number of 23 individuals with DS, aged 5.54 to 28.9 years, participated in this study and completed 6 months of training. The application was trained to consistently recognize at least 20 different unintelligible words (e.g., nouns and/or short phrases)/person. Results: Results revealed good usability and high levels of satisfaction related to the application use. Moreover, we registered improvement in linguistic abilities, particularly naming. Discussion: These results paves the road for a potential role of Talkitt application as a supportive and rehabilitative tool for DS.

Indexed as

digital applicationlanguagemachine learningspeechtrisomy 21

Identifiers

PMID37346421
PMCPMC10279874
OpenAlexW4379536586

What OpenQuestion holds

Textmetadata
LicenceCC BY
Read underepoch 390

Registered trials

None linked

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.