--- title: "ALBA — paper by Themistocleous and Stark (2026)" description: "The authors present ALBA (Automated Language Biomarker Application), a web tool built into the Open Brain AI platform. 2 references." authors: ["Charalambos Themistocleous", "Brielle C. Stark"] year: 2026 venue: "Proceedings of the Sixth Resources and ProcessIng of linguistic, para-linguistic and extra-linguistic Data from people with various forms of cognitive/psychiatric/developmental impairments in cooperation with the MENTAL.ai consortium" source: "https://aclanthology.org/2026.rapid-1.4/" doi: "10.63317/449fwsyjuzbp" licence: "CC BY-NC 4.0 (ELRA, LREC proceedings)" licence_url: "https://creativecommons.org/licenses/by-nc/4.0/" summary_licence: "Elamur Cosmic License" canonical: "https://research.elamur.ai/free/en/papers/themistocleous-2026-alba-automated-framework-benchmarking-clinical/" --- [Elamur Research](https://md.research.elamur.ai/free/en/) · [this page in HTML](https://research.elamur.ai/free/en/papers/themistocleous-2026-alba-automated-framework-benchmarking-clinical/) [home](https://md.research.elamur.ai/free/en/) / [papers](https://md.research.elamur.ai/free/en/papers/) / [2026](https://md.research.elamur.ai/free/en/papers/2026/page/22/) / ALBA: An Automated Framework for Benchmarking Clinical Language Biomarkers against Standardized Corpora # ALBA: An Automated Framework for Benchmarking Clinical Language Biomarkers against Standardized Corpora **Authors:** Charalambos Themistocleous and Brielle C. Stark · **Year:** 2026 · **Venue:** [Proceedings of the Sixth Resources and ProcessIng of linguistic, para-linguistic and extra-linguistic Data from people with various forms of cognitive/psychiatric/developmental impairments in cooperation with the MENTAL.ai consortium](https://md.research.elamur.ai/free/en/venues/rapid/) ([Resources and ProcessIng of linguistic, para-linguistic and extra-linguistic Data from people with various forms of cognitive/psychiatric/developmental impairments in cooperation with the MENTAL.ai consortium 2026](https://md.research.elamur.ai/free/en/venues/rapid/2026/)) · **Publisher:** [European Language Resources Association (ELRA)](https://md.research.elamur.ai/free/en/publishers/european-language-resources-association-elra/) · **Licence:** [CC BY-NC 4.0 (ELRA, LREC proceedings)](https://creativecommons.org/licenses/by-nc/4.0/) **Links:** [Publisher's page](https://aclanthology.org/2026.rapid-1.4/) · [PDF](https://aclanthology.org/2026.rapid-1.4.pdf) · [DOI 10.63317/449fwsyjuzbp](https://doi.org/10.63317/449fwsyjuzbp) · [OpenAlex](https://openalex.org/W7166517388) **Citations:** 0 citations (OpenAlex, 2026-10-14) ## Summary Automated software can now extract many quantitative measures from patients' connected speech. Clinicians still struggle to interpret an individual score without norms produced by the same methods. The authors present ALBA (Automated Language Biomarker Application), a web tool built into the Open Brain AI platform. It compares one patient's language measure with reference distributions drawn from standardized clinical corpora, mainly AphasiaBank and other TalkBank repositories. The reference values and the clinician's data come from the same elicitation tasks (e.g., cookie theft, Cinderella story) and the same Open Brain AI processing pipeline, so the comparison is not distorted by differences between tools. ALBA does not reprocess transcripts. It stores precomputed summary statistics for each task–diagnosis–measure combination and then automatically chooses either a one-sample t-test or a Wilcoxon-based non-parametric test, depending on whether the reference distribution is normal. Output includes a p-value, an APA-style textual interpretation, and box, bar or violin plots. The tool makes normative benchmarking of discourse measures quick and accessible, supporting differential diagnosis, therapy planning and baseline tracking. ## Key points - Reference cohorts include healthy controls and several clinical groups: aphasia subtypes, LHD, RHD, TBI, MCI and dementia. Norms are derived from more than 600 transcripts sourced from AphasiaBank/TalkBank. - Each Task × Diagnosis × Linguistic Variable cell stores eleven precomputed metrics, including mean, SD, median, min/max, Q1/Q3, Shapiro-Wilk p-value and skewness. Together these set an IsNormal flag. - Test choice works as follows: - A t-test is used if Shapiro-Wilk p > .05, or if n ≥ 30 with low skewness. - A Wilcoxon signed-rank approximation is used otherwise, including when |µ − M| > 0.1µ. - Results are labeled "Significant" or "Similar" at α = 0.05. - Computation runs client-side with the jStat library, so the patient's value never leaves the browser. - Aggregated norms for 290 linguistic biomarkers are released as a machine-readable CSV via openbrainai.com. Raw transcripts remain under TalkBank's registration-based access agreement. *Our summary of the paper, in our own words — not its text. The work belongs to its authors; read it at the links above.* ## Institutions - [University of Oslo](https://md.research.elamur.ai/free/en/universities/university-of-oslo/) — University, Oslo, Norway · 51 works · 4,155 citations - [Indiana University Bloomington](https://md.research.elamur.ai/free/en/universities/indiana-university-bloomington/) — University, Bloomington, United States · 40 works · 4,003 citations - [Indiana University](https://md.research.elamur.ai/free/en/universities/indiana-university/) — University, Bloomington, United States · 42 works · 3,981 citations 📚 Shelves (8): [🎭 Arts and Humanities](https://md.research.elamur.ai/free/en/shelves/arts-and-humanities/) · 17,450 works · [🗣️ Language and Linguistics](https://md.research.elamur.ai/free/en/shelves/arts-and-humanities/language-and-linguistics/) · 17,296 works · [💭 Psychology](https://md.research.elamur.ai/free/en/shelves/psychology/) · 1,649 works · [💭 Social Psychology](https://md.research.elamur.ai/free/en/shelves/psychology/social-psychology/) · 330 works · [🩺 Medicine](https://md.research.elamur.ai/free/en/shelves/medicine/) · 275 works · [🧠 Neuroscience](https://md.research.elamur.ai/free/en/shelves/neuroscience/) · 186 works · [🧠 Cognitive Neuroscience](https://md.research.elamur.ai/free/en/shelves/neuroscience/cognitive-neuroscience/) · 185 works · [🩺 Psychiatry and Mental health](https://md.research.elamur.ai/free/en/shelves/medicine/psychiatry-and-mental-health/) · 9 works ## Cite Cite as: Charalambos Themistocleous and Brielle C. Stark. 2026. ALBA: An Automated Framework for Benchmarking Clinical Language Biomarkers against Standardized Corpora. Proceedings of the Sixth Resources and ProcessIng of linguistic, para-linguistic and extra-linguistic Data from people with various forms of cognitive/psychiatric/developmental impairments in cooperation with the MENTAL.ai consortium. The paper itself, not this page. BibTeX from the library's record of the work. ```bibtex @inproceedings{themistocleous2026alba, title = {{ALBA: An Automated Framework for Benchmarking Clinical Language Biomarkers against Standardized Corpora}}, author = {Charalambos Themistocleous and Brielle C. Stark}, booktitle = {Proceedings of the Sixth Resources and ProcessIng of linguistic, para-linguistic and extra-linguistic Data from people with various forms of cognitive/psychiatric/developmental impairments in cooperation with the MENTAL.ai consortium}, year = {2026}, doi = {10.63317/449fwsyjuzbp}, url = {https://doi.org/10.63317/449fwsyjuzbp} } ``` - [← previous Al-Warraq at AR-MS NAKBA-NLP 2026: Adapting Vision-Language and Transformer Models for Automatic Manuscript OCR/HTR](https://md.research.elamur.ai/free/en/papers/youssef-2026-al-warraq-ar-ms-nakba/) - [next → ALDEN: Reinforcement Learning for Active Navigation and Evidence Gathering in Long Documents](https://md.research.elamur.ai/free/en/papers/yang-2026-alden-reinforcement-learning-active-navigation/) - [↑ back to papers of 2026](https://md.research.elamur.ai/free/en/papers/2026/page/22/) ## References 2 references, 0 of them with a card of ours. ↗ leads to the work, «find» searches for one we have no id for yet. 1. S. Bengio and G. Heigold. Word embeddings for speech recognition. In Proceedings of the Annual Conference of the International Speech Communication Association, INTERSPEECH, pages 1053–1057. Export Date: 20 February 2015. [find](https://scholar.google.com/scholar?q=S%2E+Bengio+and+G%2E+Heigold%2E+Word+embeddings+for+speech+recognition%2E+In+Proceedings+of+the+Annual+Conference+of+the+International+Speech+Communication+Association%2C+INTERSPEECH%2C+pages+1053%E2%80%931057%2E+Export+Da) 2. Lucy Bryant, Alison Ferguson, and Elizabeth Spencer. 2016. Linguistic analysis of discourse in aphasia: A review of the literature. Clinical linguistics phonetics, 30(7):489–518. \#\# Conclusion [find](https://scholar.google.com/scholar?q=Lucy+Bryant%2C+Alison+Ferguson%2C+and+Elizabeth+Spencer%2E+2016%2E+Linguistic+analysis+of+discourse+in+aphasia%3A+A+review+of+the+literature%2E+Clinical+linguistics+phonetics%2C+30%287%29%3A489%E2%80%93518%2E+%5C%23%5C%23+Conclusion) *Updated 1 November 2026*