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Pre-linguistic segmentation of speech into syllable-like units
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Syllables are often considered to be central to infant and adult speech perception. Many theories and behavioral studies on early language acquisition are also based on syllable-level representations of spoken language. There is little clarity, however, on what sort of pre-linguistic “syllable” would actually be accessible to an infant with no phonological or lexical knowledge. Anchored by the notion that syllables are organized around particularly sonorous (audible) speech sounds, the present study investigates the feasibility of speech segmentation into syllable-like chunks without any a priori linguistic knowledge. We first operationalize sonority as a measurable property of the acoustic input, and then use sonority variation across time, or speech rhythm, as the basis for segmentation. The entire process from acoustic input to chunks of syllable-like acoustic segments is implemented as a computational model inspired by the oscillatory entrainment of the brain to speech rhythm. We analyze the output of the segmentation process in three different languages, showing that the sonority fluctuation in speech is highly informative of syllable and word boundaries in all three cases without any language-specific tuning of the model. These findings support the widely held assumption that syllable-like structure is accessible to infants even when they are only beginning to learn the properties of their native language.
Title: Pre-linguistic segmentation of speech into syllable-like units
Description:
Syllables are often considered to be central to infant and adult speech perception.
Many theories and behavioral studies on early language acquisition are also based on syllable-level representations of spoken language.
There is little clarity, however, on what sort of pre-linguistic “syllable” would actually be accessible to an infant with no phonological or lexical knowledge.
Anchored by the notion that syllables are organized around particularly sonorous (audible) speech sounds, the present study investigates the feasibility of speech segmentation into syllable-like chunks without any a priori linguistic knowledge.
We first operationalize sonority as a measurable property of the acoustic input, and then use sonority variation across time, or speech rhythm, as the basis for segmentation.
The entire process from acoustic input to chunks of syllable-like acoustic segments is implemented as a computational model inspired by the oscillatory entrainment of the brain to speech rhythm.
We analyze the output of the segmentation process in three different languages, showing that the sonority fluctuation in speech is highly informative of syllable and word boundaries in all three cases without any language-specific tuning of the model.
These findings support the widely held assumption that syllable-like structure is accessible to infants even when they are only beginning to learn the properties of their native language.
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