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How much does prosody help word segmentation? A simulation study on infant-directed speech
- Source :
- Cognition, Cognition, 2022, 219, pp.104961. ⟨10.1016/j.cognition.2021.104961⟩, Cognition, Elsevier, 2022, 219, pp.104961. ⟨10.1016/j.cognition.2021.104961⟩
- Publication Year :
- 2022
- Publisher :
- Elsevier, 2022.
-
Abstract
- International audience; Infants come to learn several hundreds of word forms by two years of age, and it is possible this involves carving these forms out from continuous speech. It has been proposed that the task is facilitated by the presence of prosodic boundaries. We revisit this claim by running computational models of word segmentation, with and without prosodic information, on a corpus of infant-directed speech. We use five cognitively-based algorithms, which vary in whether they employ a sub-lexical or a lexical segmentation strategy and whether they are simple heuristics or embody an ideal learner. Results show that providing expert-annotated prosodic breaks does not uniformly help all segmentation models. The sub-lexical algorithms, which perform more poorly, benefit most, while the lexical ones show a very small gain. Moreover, when prosodic information is derived automatically from the acoustic cues infants are known to be sensitive to, errors in the detection of the boundaries lead to smaller positive effects, and even negative ones for some algorithms. This shows that even though infants could potentially use prosodic breaks, it does not necessarily follow that they should incorporate prosody into their segmentation strategies, when confronted with realistic signals.
- Subjects :
- Linguistics and Language
Cognitive Neuroscience
Speech recognition
Experimental and Cognitive Psychology
Prosody
Infant-directed speech
050105 experimental psychology
Language and Linguistics
Speech Acoustics
Task (project management)
Infant language acquisition
Developmental and Educational Psychology
Humans
Learning
Speech
0501 psychology and cognitive sciences
Segmentation
Computer Simulation
ComputingMilieux_MISCELLANEOUS
Computational model
05 social sciences
Text segmentation
Infant
acquisition
[SCCO.LING]Cognitive science/Linguistics
Word segmentation
[SCCO.PSYC]Cognitive science/Psychology
Speech Perception
Infant language
Cues
Heuristics
Psychology
Word (computer architecture)
050104 developmental & child psychology
Subjects
Details
- Language :
- English
- ISSN :
- 00100277 and 18737838
- Database :
- OpenAIRE
- Journal :
- Cognition, Cognition, 2022, 219, pp.104961. ⟨10.1016/j.cognition.2021.104961⟩, Cognition, Elsevier, 2022, 219, pp.104961. ⟨10.1016/j.cognition.2021.104961⟩
- Accession number :
- edsair.doi.dedup.....efb86f499c0bf816049c73868aefb6a9