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Everyday Speech May Reveal Early Cognitive Decline - Neuroscience News
Summary: Researchers found that everyday speech timing -- including pauses, fillers, and subtle patterns -- strongly reflects executive function, a key cognitive system that supports memory and flexible thinking. Using AI to analyze natural speech, the study showed that these linguistic features can predict cognitive-test performance independent of age, sex, or education. Because speech is effortless to collect and free from practice effects, it offers a scalable way to monitor early brain changes tied to dementia risk. The findings highlight natural speech as a promising tool for early detection and long-term tracking of cognitive decline. The way we speak in everyday conversation may hold important clues about brain health, according to new research from Baycrest, the University of Toronto and York University. The study found that subtle features of speech timing, such as pauses, fillers ('uh,' 'um') and word-finding difficulty, are strongly linked to executive function, the set of mental skills that support memory, planning and flexible thinking. The study is one of the first to demonstrate a direct link between natural speech patterns and essential cognitive functions, opening new avenues of research to better understand the mind. It builds on previous research that showed that faster talking speed is linked to preserved thinking in older adults (Wei et al., 2024). "The message is clear: speech timing is more than just a matter of style, it's a sensitive indicator of brain health," says Dr. Jed Meltzer, Senior Scientist at Baycrest's Rotman Research Institute and senior author on this study, titled "Natural Speech Analysis Can Reveal Individual Differences in Executive Function Across the Adult Lifespan." Participants were asked to describe complex pictures in their own words while also completing standard tests of executive function. Using artificial intelligence, researchers analyzed the recordings and identified hundreds of subtle features, including pauses, filler words and timing patterns. These features reliably predicted performance on cognitive tests, even after accounting for age, sex and education. Executive functions decline with age and are often compromised early in dementia, but they are hard to track with traditional testing, which is time-consuming and vulnerable to practice effects, the improvements in performance due to familiarity. Natural speech, by contrast, is an everyday behaviour that can be measured repeatedly, unobtrusively and at scale. It also provides information about processing speed as a sensitive measure of cognitive integrity in an ecologically valid manner, without the need for imposed time limits -- something that is challenging to capture with most traditional cognitive tasks. Given the ease, convenience and sensitivity of natural speech analysis, it is an ideal choice for repeated assessments, which could identify individuals who are experiencing cognitive decline at a higher rate than expected and may be at high risk for developing dementia. "This research sets the stage for exciting opportunities to develop tools that could help track cognitive changes in clinics or even at home. Early detection is critical for any cure or intervention, as dementia involves progressive degeneration of the brain that may be slowed," says Dr. Meltzer. The researchers emphasize the need for longitudinal studies, following individuals' speech over time, to separate normal aging from early signs of disease. They note that combining naturalistic speech with other measures could make early detection of cognitive decline more precise and accessible. Funding: This research was supported by the Mitacs Accelerate program and the Natural Sciences and Engineering Research Council of Canada (NSERC). Author: Natasha Nacevski-Laird Source: Baycrest Contact: Natasha Nacevski-Laird - Baycrest Image: The image is credited to Neuroscience News Original Research: Closed access. "Natural Speech Analysis Can Reveal Individual Differences in Executive Function Across the Adult Lifespan" by Jed Meltzer et al. Journal of Speech, Language, and Hearing Research Abstract Natural Speech Analysis Can Reveal Individual Differences in Executive Function Across the Adult Lifespan Automated analysis of naturalistic speech has emerged as an effective tool for detecting cognitive decline in dementia but has seldom been used to examine the ordinary cognitive decline occurring in normal aging. Executive function (EF) declines throughout the adult lifespan but is difficult to track longitudinally due to practice effects, making speech-based assessments particularly attractive. This study examined relationships between EF and speech characteristics. We collected two audio picture descriptions from participants in two experiments that also included EF assessments, with 67 healthy older adults (aged 65-75 years) in Study 1 and 174 healthy adults (aged 18-90 years) in Study 2. Language composite scores were computed by aggregating relevant speech features indexing aspects of speech that have been reported to show changes in pathological aging. Principal components reflecting common covariation in speech features were extracted from a large training data set to compute speech domain scores. The relationships between language composites/speech principal components and EF were assessed while controlling for age, gender, and education. In Study 1, older adults' word-finding difficulties, measured as speech disfluencies, showed significant associations with EF. Study 2 confirms that speech disfluencies can explain individual differences in EF not only for adults above the age of 65 years but also across the adult lifespan. Information units and coherence in speech showed weaker associations with EF and Montreal Cognitive Assessment scores that were not significant after correction for multiple comparisons. The findings revealed associations between word-finding ability in natural speech and general EF across the adult lifespan, supporting natural speech analysis as a convenient and sensitive assessment of general cognitive ability.
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Everyday speech patterns reveal hidden markers of brain health
Baycrest Corporate Centre for Geriatric CareNov 11 2025 The way we speak in everyday conversation may hold important clues about brain health, according to new research from Baycrest, the University of Toronto and York University. The study found that subtle features of speech timing, such as pauses, fillers ('uh,' 'um') and word-finding difficulty, are strongly linked to executive function, the set of mental skills that support memory, planning and flexible thinking. The study is one of the first to demonstrate a direct link between natural speech patterns and essential cognitive functions, opening new avenues of research to better understand the mind. It builds on previous research that showed that faster talking speed is linked to preserved thinking in older adults (Wei et al., 2024). "The message is clear: speech timing is more than just a matter of style, it's a sensitive indicator of brain health," says Dr. Jed Meltzer, Senior Scientist at Baycrest's Rotman Research Institute and senior author on this study, titled "Natural Speech Analysis Can Reveal Individual Differences in Executive Function Across the Adult Lifespan." Participants were asked to describe complex pictures in their own words while also completing standard tests of executive function. Using artificial intelligence, researchers analyzed the recordings and identified hundreds of subtle features, including pauses, filler words and timing patterns. These features reliably predicted performance on cognitive tests, even after accounting for age, sex and education. Executive functions decline with age and are often compromised early in dementia, but they are hard to track with traditional testing, which is time-consuming and vulnerable to practice effects, the improvements in performance due to familiarity. Natural speech, by contrast, is an everyday behaviour that can be measured repeatedly, unobtrusively and at scale. It also provides information about processing speed as a sensitive measure of cognitive integrity in an ecologically valid manner, without the need for imposed time limits - something that is challenging to capture with most traditional cognitive tasks. Given the ease, convenience and sensitivity of natural speech analysis, it is an ideal choice for repeated assessments, which could identify individuals who are experiencing cognitive decline at a higher rate than expected and may be at high risk for developing dementia. This research sets the stage for exciting opportunities to develop tools that could help track cognitive changes in clinics or even at home. Early detection is critical for any cure or intervention, as dementia involves progressive degeneration of the brain that may be slowed." Dr. Jed Meltzer, Senior Scientist, Baycrest's Rotman Research Institute The researchers emphasize the need for longitudinal studies, following individuals' speech over time, to separate normal aging from early signs of disease. They note that combining naturalistic speech with other measures could make early detection of cognitive decline more precise and accessible. This research was supported by the Mitacs Accelerate program and the Natural Sciences and Engineering Research Council of Canada (NSERC). Baycrest Corporate Centre for Geriatric Care Journal reference: Wei, H.T., et al. (2025). Natural Speech Analysis Can Reveal Individual Differences in Executive Function Across the Adult Lifespan. Journal of Speech, Language, and Hearing Research. doi: 10.1044/2025_jslhr-24-00268. https://pubs.asha.org/doi/10.1044/2025_JSLHR-24-00268
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Researchers use artificial intelligence to analyze natural speech patterns, discovering that everyday speech timing features like pauses and fillers can predict cognitive decline and executive function performance, offering a scalable tool for early dementia detection.

Researchers from Baycrest, the University of Toronto, and York University have made a significant breakthrough in early detection of cognitive decline by demonstrating that artificial intelligence can analyze everyday speech patterns to reveal crucial information about brain health. The study, published in the Journal of Speech, Language, and Hearing Research, shows that subtle features of natural speech timing serve as sensitive indicators of executive function - the cognitive system responsible for memory, planning, and flexible thinking
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.The research team employed artificial intelligence to analyze natural speech recordings from participants who were asked to describe complex pictures in their own words while simultaneously completing standard executive function tests. The AI system identified hundreds of subtle linguistic features, including pauses, filler words like 'uh' and 'um,' word-finding difficulties, and various timing patterns within natural speech
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.Dr. Jed Meltzer, Senior Scientist at Baycrest's Rotman Research Institute and senior author of the study, emphasized the significance of these findings: "The message is clear: speech timing is more than just a matter of style, it's a sensitive indicator of brain health"
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.The study's most remarkable finding was that these speech-derived features could reliably predict performance on cognitive tests, even after accounting for traditional demographic factors such as age, sex, and education level. This represents a significant advancement over conventional cognitive assessment methods, which are often time-consuming, expensive, and subject to practice effects - improvements in performance due to repeated exposure to the same tests
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.The research involved two separate experiments: Study 1 included 67 healthy older adults aged 65-75 years, while Study 2 encompassed 174 healthy adults across a broader age range of 18-90 years, providing robust validation across different age groups
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Natural speech analysis offers several advantages over traditional cognitive testing methods. Unlike conventional assessments, speech can be collected effortlessly, repeatedly, and unobtrusively, making it ideal for large-scale monitoring programs. The technology provides information about processing speed as a sensitive measure of cognitive integrity in an ecologically valid manner, without requiring imposed time limits that characterize most traditional cognitive tasks
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.This scalability is particularly important given that executive functions decline with age and are often compromised early in dementia progression. The ability to conduct repeated assessments could help identify individuals experiencing cognitive decline at rates higher than expected, potentially flagging those at high risk for developing dementia before clinical symptoms become apparent
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.The research team acknowledges that longitudinal studies following individuals' speech patterns over extended periods will be crucial for distinguishing normal aging processes from early disease indicators. Dr. Meltzer noted that "this research sets the stage for exciting opportunities to develop tools that could help track cognitive changes in clinics or even at home. Early detection is critical for any cure or intervention, as dementia involves progressive degeneration of the brain that may be slowed"
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.The researchers suggest that combining naturalistic speech analysis with other biomarkers and assessment measures could enhance the precision and accessibility of early cognitive decline detection, potentially revolutionizing how healthcare providers monitor brain health across populations.
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