ArticleScientific data2026
SONIVA database: Speech recognition validation in aphasia.
Article in Scientific data, 2026. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Cited by 1 paper.
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.
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.
Who cites it
1 citing paper in PubMed.
- SONIVA database: Speech recognition validation in aphasia.Scientific data · 2026Article
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.
Funding
Abstract
Post-stroke aphasia is a major contributor to language impairment and neuro-disability worldwide, making automated assessment a critical research priority. However, clinically validated automatic speech recognition (ASR) systems remain limited by the scarcity of large, annotated datasets capturing aphasia's heterogeneous manifestations. We introduce SONIVA (Speech recOgNItion Validation in Aphasia), the largest and most comprehensively curated database for validating speech recognition in aphasia, comprising audio recordings from approximately 1,000 stroke survivors and 6,000 age-matched controls. The dataset comprises annotated speech from 571 stroke survivors, 103 of whom contributed longitudinal recordings (mean age: 60.65 ± 12.97 years; 68.77% male), and 103 controls (mean age: 59.64 ± 11.48 years; 62.05% male). These recordings are enriched with detailed linguistic coding, orthographic transcriptions, and International Phonetic Alphabet annotations. Foundation models fine-tuned on SONIVA correlate strongly with expert transcriptions (Spearman's r = 0.79-0.86; p < 0.0001), while acoustic classifiers achieve 93% stroke classification accuracy, enabling scalable analysis for rehabilitation and clinical assessment.
Indexed as
Identifiers
What OpenQuestion holds
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.