Evidence map›Paper›PMID 39700465›Full record

ArticleJournal of speech, language, and hearing research : JSLHR2025

Vocal and Facial Behavior During Affect Production in Autism Spectrum Disorder.

Hardik Kothare, Vikram Ramanarayanan, Michael Neumann, Jackson Liscombe, Vanessa Richter, Linnea Lampinen, Alison Bai, Cristian Preciado, Katherine Brogan, Carly Demopoulos

Abstract read
In one paragraph

Article in Journal of speech, language, and hearing research : JSLHR, 2025. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Cited by 2 papers.

0numbers the graph read from it
0cells of the map it votes in
2citing papers in PubMed
–field-weighted citation impact
1 · What the graph read from it

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.

2 · The registry

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.

3 · Its place in the literature

Who cites it

2 citing papers in PubMed.

  1. Article
  2. Article
4 · The record

Corrections and comments

PubMed lists nothing against this paper. Absence here is not a guarantee, only a check that was made.

5 · Who and what money

Authors and funding

10 authors.

Hardik KothareModality.AI, Inc., San Francisco, CA.ORCID 0000-0003-4305-0334
Vikram RamanarayananModality.AI, Inc., San Francisco, CA.ORCID 0000-0001-7810-2769
Michael NeumannModality.AI, Inc., San Francisco, CA.
Jackson LiscombeModality.AI, Inc., San Francisco, CA.
Vanessa RichterModality.AI, Inc., San Francisco, CA.
Linnea LampinenUniversity of California, San Francisco.
Alison BaiUniversity of California, San Francisco.
Cristian PreciadoUniversity of California, San Francisco.
Katherine BroganUniversity of California, San Francisco.
Carly DemopoulosUniversity of California, San Francisco.

Funding

Neural mechanisms of speech motor control in Autism Spectrum DisordersR01DC019167 · NIDCD · UNIVERSITY OF CALIFORNIA, SAN FRANCISCO · PI DEMOPOULOS, CARLY, LI, YAN · 2021 to 2025
$4.2M
Vocal sensorimotor control and voice abnormalities in Autism Spectrum DisordersK23DC016637 · NIDCD · UNIVERSITY OF CALIFORNIA, SAN FRANCISCO · PI DEMOPOULOS, CARLY · 2018 to 2022
$1.0M
NIDCD NIH HHS K23 DC016637NIDCD NIH HHS R01 DC019167
6 · The paper itself

Abstract

purposeWe investigate the extent to which automated audiovisual metrics extracted during an affect production task show statistically significant differences between a cohort of children diagnosed with autism spectrum disorder (ASD) and typically developing controls.

methodForty children with ASD and 21 neurotypical controls interacted with a multimodal conversational platform with a virtual agent, Tina, who guided them through tasks prompting facial and vocal communication of four emotions-happy, angry, sad, and afraid-under conditions of high and low verbal and social cognitive task demands.

resultsIndividuals with ASD exhibited greater standard deviation of the fundamental frequency of the voice with the minima and maxima of the pitch contour occurring at an earlier time point as compared to controls. The intensity and voice quality of emotional speech were also different between the two cohorts in certain conditions. Additionally, facial metrics capturing the acceleration of the lower lip, lip width, eye opening, and vertical displacement of the eyebrows were also important markers to distinguish between children with ASD and neurotypical controls. Both facial and speech metrics performed well above chance in group classification accuracy.

conclusionSpeech acoustic and facial metrics associated with affect production were effective in distinguishing between children with ASD and neurotypical controls. SUPPLEMENTAL MATERIAL: https://doi.org/10.23641/asha.28027796.

Indexed as

Autism Spectrum DisorderFacial ExpressionSpeechVoiceAdolescentCase-Control StudiesChildChild, PreschoolEmotionsFemaleHumansMaleSpeech AcousticsVoice Quality

Identifiers

PMID39700465
PMCPMC12381824

What OpenQuestion holds

Textmetadata
LicenceCC BY-NC
Read underepoch 390

Registered trials

None linked

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.