# Novel Computational Analysis of Prosody in ASD and the Broad Autism Phenotype

> **NIH NIH R03** · NORTHWESTERN UNIVERSITY · 2021 · $74,639

## Abstract

Abstract
 Pragmatic (i.e., social) language impairments are a core feature of Autism Spectrum Disorder (ASD), and
differences have also been observed more subtly in the Broad Autism Phenotype (BAP; a cluster of subclinical
features related to ASD, which are believed to reflect genetic liability in clinically unaffected relatives). Prosody
is a central component of pragmatics, which includes aspects of speech and language that modulate and
enhance meaning at grammatical, pragmatic, and affective levels including stress and intonation, which are
conveyed by changes in fundamental frequency, intensity, and rate. Atypical prosody in ASD has been
identified as the most prominent feature that immediately identifies an individual with ASD as “odd” compared
to typically developing peers, causing significant obstacles to social interaction and integration1-3. More subtle
differences in prosody have also been observed among parents of individuals with ASD, and may serve as a
key marker of ASD genetic risk, measurable in affected and unaffected individuals. Because speech samples
may be easily obtained, identification of key prosodic profiles in ASD and profiles reflecting genetic liability to
ASD, could have widespread implication as a biomarker for detection of ASD risk, and as a tool for
assessment and interventions focused on this clinically significant feature of ASD. Limitations in current work
pose significant barriers to the objective and efficient characterization of prosody, where current methods
typically rely on subjective perceptual ratings which, though clinically valid, are difficult to obtain and apply
objectively in treatment contexts, and are unfeasible for application with large samples. Moreover, without
extensive training, perceptual rating methods are not adequately sensitive for capturing important variation and
heterogeneity in ASD prosodic profiles, or identifying the often quite subtle yet biologically meaningful prosodic
differences that may be observed in clinically unaffected relatives. These factors together impose substantial
barriers to reproducibility, limit scalability, and render prosodic characterization unfeasible for use by clinicians.
This project attempts to address these challenges by applying sophisticated computational modeling of
extensive existing speech and language samples collected through a larger companion project
(R01DC010191, PI: Losh), to characterize prosodic profiles in ASD and in parents. In Preliminary Data, we
demonstrate evidence of distinct prosodic profiles of individuals with ASD and parents, along with relationships
to broader pragmatic language abilities and neural processing of speech sounds in ASD and parents,
supporting the goals of this project to apply sophisticated computational tools to speech data obtained across
multiple contexts in order to 1) identify prosodic profiles that characterize ASD and the BAP in parents, and 2)
examine how prosodic profiles relate to broader clinical-behavi...

## Key facts

- **NIH application ID:** 10113580
- **Project number:** 5R03DC018644-02
- **Recipient organization:** NORTHWESTERN UNIVERSITY
- **Principal Investigator:** Molly C Losh
- **Activity code:** R03 (R01, R21, SBIR, etc.)
- **Funding institute:** NIH
- **Fiscal year:** 2021
- **Award amount:** $74,639
- **Award type:** 5
- **Project period:** 2020-04-01 → 2023-03-31

## Primary source

NIH RePORTER: https://reporter.nih.gov/project-details/10113580

## Citation

> US National Institutes of Health, RePORTER application 10113580, Novel Computational Analysis of Prosody in ASD and the Broad Autism Phenotype (5R03DC018644-02). Retrieved via AI Analytics 2026-05-23 from https://api.ai-analytics.org/grant/nih/10113580. Licensed CC0.

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