Science

Detect changes in neurological and psychiatric symptoms faster, more easily, and more objectively through speech with the help of natural language processing and artificial intelligence.

Scientific Overview

Disease monitoring in neuroscience is hampered by insensitive clinical scales which may not detect subtle changes in symptoms. By extracting over 550 features of speech and language, Winterlight Labs’ technology can measure fine-grained changes that traditional assessments cannot.

Our features and algorithms can be used in health research to help identify disease, track change over time, monitor disease severity, and detect response to treatment. Winterlight’s technology has been used to study neurodegenerative and psychiatric diseases and disorders, including Alzheimer’s Disease, Mild Cognitive Impairment, Frontotemporal Dementia, Parkinson’s Disease, Depression, Schizophrenia and more.

Speech in Alzheimer's Disease

Speech symptoms in Alzheimer’s disease include changes to the rate and rhythm of speech as well as its content and organization. Winterlight’s technology can be used to quantify these changes in order to detect signs of Alzheimer’s disease, monitor disease progression and measure response to treatments and therapies in clinical trials and other healthcare settings.

Recommended Speech Assessments

Comprehensive (up to every 6 months)

  • Paragraph reading
  • Picture description x2
  • Phonemic fluency
  • Semantic fluency
  • Journaling
  • Paragraph Recall

Brief (up to weekly, varying stimuli)

  • Picture description x2
  • Journaling

Speech Features Of Interest

Selected speech features that differ in Alzheimer’s disease:

  • Information content: Reduced number of correctly described items in picture description tasks
  • Coherence: Reduced semantic relatedness of descriptions to picture stimuli
  • Repetition: More similar or repetitive utterances
  • Use of prepositions: Reduced use of prepositions, which are relational words like "on", "over", or "under"
  • Use of pronouns: Increased use of pronouns, like "this", "that", or "it"

Select Publications

Digital remote assessment of speech acoustics in cognitively unimpaired adults: feasibility, reliability and associations with amyloid pathology

van den Berg R., de Boer C., Zwan M.D., Jutten R.J., van Liere M., van de Glind M-C.A.B.J., Dubbelman M.A., Schlüter L.M., van Harten A.C., Teunissen C.E., van de Giessen E., Barkhof F., Collij L.E., Robin J., Simpson W., Harrison J.E., van der Flier W.M., Sikkes S.A.M. (2024)

Alzheimer's Research & Therapy.

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Robustness and generalizability of a speech- based digital biomarker derived from recordings of the Clinical Dementia Rating (CDR) interview

Spilka M., Xu M., Toth B., Hashemifar S., Amora R., Robin J., Teng E., Monteiro C., Simpson W. (2024)

Alzheimer's Association International Conference (AAIC).

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Linguistic changes in neurodegenerative diseases relate to clinical symptoms

Gumus M., Koo M., Studzinski C.M., Bhan A., Robin J., Black S.E. (2024)

Frontiers in Neurology.

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Leveraging speech production as a physiological marker of cognitive decline: Demonstration of the role of timing and acoustic changes

Sorinas J., Huynh M.T.D., Hannesdottir K., Robin J., Simpson W., Coello N., Caputo A., Riviere M.-E., Curcic J. (2024)

International Conference on Alzheimer’s and Parkinson’s Diseases and related neurological disorders (AD/PD 2024).

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Generalizability and Robustness of Large Language Models Detecting Alzheimer’s Disease from Speech.

Novikova J. (2023)

GenBench at EMNLP (Empirical Methods in Natural Language Processing) International Conference.

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How Much Speech Data Is Needed for Tracking Language Change in Alzheimer’s Disease? A Comparison of Random Length, 5-Min, and 1-Min Spontaneous Speech Samples.

Petti U., Baker S., Korhonen A., Robin J. (2023)

Digital Biomarkers.

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Robustness and generalizability of a speech based composite score for measuring disease progression in AD.

Spilka M., Xu M., Robin J., Simpson W. (2023)

Clinical Trials on Alzheimer’s Disease (CTAD) Conference.

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Automated detection of progressive speech changes in early Alzheimer's disease.

Robin J., Xu M., Balagopalan A., Novikova J., Kahn L., Oday A., Hejrati M., Hashemifar S., Negahdar M., Simpson W., Teng E. (2023)

Alzheimer's & Dementia: Diagnosis, Assessment & Disease Monitoring.

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Speech phenotypes in cognitively healthy participants at risk of developing Alzheimer’s disease.

Sorinas J., Robin J., Simpson W., Curcic J., Hannesdottir K. (2023)

International Conference on Alzheimer's and Parkinson's Diseases (ADPD).

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The generalizability of longitudinal changes in speech before Alzheimer’s Disease diagnosis.

Petti U., Baker S., Korhonen A., Robin J. (2023)

Journal of Alzheimer's Disease.

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Validation of an objective, speech-based object content score for measuring disease progression in AD.

Robin J., Xu M., Detke, M., Simpson W. (2022)

Clinical Trials in Alzheimer's Disease.

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Description of the Method for Evaluating Digital Endpoints in Alzheimer Disease Study: Protocol for an Exploratory, Cross-sectional Study.

Curcic J., Vallejo V., Sorinas J., Sverdlov O., Praestgaard J., Piksa M., Deurinck M., Erdemli G., Bugler M., Tarnanas I., Taptiklis N., Cormack F., Anker R., Masse F., Souillard-Mandar W., Intrator N., Molcho L., Madero E., Bott N., Chambers M., Tamory J., Shulz M., Fernandez G., Simpson W., Robin J., Snaedal JG., Cha J., Hannesdottir K. (2022)

JMIR Research Protocols.

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Characterizing progressive speech changes in prodromal-to-mild Alzheimer’s disease using natural language processing.

Robin J., Xu M., Balagopalan A., Novikova J., Kahn L., Oday A., Hejrati M., Hashemifar S., Negahdar M., Simpson W., Teng E. (2022)

Alzheimer's Association International Conference.

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Association Between Speech Characteristics And Cortical [18F]GTP1 Tau PET Tau Levels In Prodromal-To-Mild Alzheimer’s Disease

Robin J., Xu M., Balagopalan A., Novikova J., Hashemifar S., Oday A., Kahn L., Hejrati M., Amora R., Bohorquez S.S., Simpson W., Teng E. (2022)

Alzheimer's & Parkinson's Diseases Conference.

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Using Digital Speech Assessments to Detect Early Signs of Cognitive Impairment.

Robin J., Xu M., Kaufman L.D., Simpson W. (2021)

Frontiers in Digital Health.

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Correlating natural language processing and automated speech analysis with clinician assessment to quantify speech-language changes in mild cognitive impairment and Alzheimer’s dementia.

Yeung A., Iaboni A., Rochon E., Lavoie M., Santiago C., Yancheva M., Novikova J., Xu M., Robin J., Kaufman L.D., Mostafa F. (2021)

Alzheimer's Research & Therapy.

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Comparing Pre-trained and Feature-Based Models for Prediction of Alzheimer's Disease Based on Speech

Balagopalan A., Eyre B., Robin J., Rudzicz F., Novikova J. (2021)

Frontiers in Aging Neuroscience.

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Evaluation of speech-based digital biomarkers for Alzheimer’s Disease.

Robin J., Kaufman L.D., Simpson W. (2020)

Clinical Trials on Alzheimer’s Disease.

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Linguistic features identify Alzheimer’s disease in narrative speech

Fraser K., Meltzer J., Rudzicz F. (2015)

Journal of Alzheimer's Disease, 49(2), 407-422.

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