ArticleNature human behaviour2023
Deep learning reveals what vocal bursts express in different cultures.
Article in Nature human behaviour, 2023. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Cited by 9 papers.
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.
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.
Who cites it
9 citing papers in PubMed.
- The expression of awe: evolutionary origins and cultural elaborations of a basic emotion.Philosophical transactions of the Royal Society of London. Series B, Biological sciences · 2026Review
- Decoding Gender in Cough Sounds: A Transformer-Based Analysis.The Laryngoscope · 2026Article
- Speak or shout? Nonverbal vocalizations promote rapid detection of emotions in vocal communication.PloS one · 2026Article
- The analysis of international communication value assessment of Chinese mythology themed animated films in belt and road under BPNN algorithm.Scientific reports · 2025Article
- Structure in conversation: Evidence for the vocabulary, semantics, and syntax of prosody.Proceedings of the National Academy of Sciences of the United States of America · 2025Article
- Vocal performance evaluation of the intelligent note recognition method based on deep learning.Scientific reports · 2025Article
- Naturalistic multimodal emotion data with deep learning can advance the theoretical understanding of emotion.Psychological research · 2024Review
- Facial expression recognition (FER) survey: a vision, architectural elements, and future directions.PeerJ. Computer science · 2024Article
- The nature and neurobiology of fear and anxiety: State of the science and opportunities for accelerating discovery.Neuroscience and biobehavioral reviews · 2023Review
Corrections and comments
PubMed lists nothing against this paper. Absence here is not a guarantee, only a check that was made.
Authors and funding
11 authors.
Funding
No grant is acknowledged in the PubMed record.
Abstract
Human social life is rich with sighs, chuckles, shrieks and other emotional vocalizations, called 'vocal bursts'. Nevertheless, the meaning of vocal bursts across cultures is only beginning to be understood. Here, we combined large-scale experimental data collection with deep learning to reveal the shared and culture-specific meanings of vocal bursts. A total of n = 4,031 participants in China, India, South Africa, the USA and Venezuela mimicked vocal bursts drawn from 2,756 seed recordings. Participants also judged the emotional meaning of each vocal burst. A deep neural network tasked with predicting the culture-specific meanings people attributed to vocal bursts while disregarding context and speaker identity discovered 24 acoustic dimensions, or kinds, of vocal expression with distinct emotion-related meanings. The meanings attributed to these complex vocal modulations were 79% preserved across the five countries and three languages. These results reveal the underlying dimensions of human emotional vocalization in remarkable detail.
Indexed as
Identifiers
36577898What OpenQuestion holds
Registered trials
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.