Structural packaging in the input to language learning: Contributions of prosodic and morphological marking of phrases to the acquisition of language

Morgan, James L.; Meier, Richard P.; Newport, Elissa L.

doi:10.1016/0010-0285(87)90017-x

Cited by 226 publications

(218 citation statements)

References 38 publications

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“…Our findings thus lend support to arguments that prosodic cues, which signal constituent edges, are critical for acquiring word forms and grammatical patterns in infants and adults (34)(35)(36)(37)(38)(39)(40).…”

Section: (C-e) Speech Waveforms Pitch Tracks and Syllable Duratiosupporting

confidence: 81%

Prosody guides the rapid mapping of auditory word forms onto visual objects in 6-mo-old infants

Shukla

White

Aslin

2011

Proc. Natl. Acad. Sci. U.S.A.

182

157

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Human infants are predisposed to rapidly acquire their native language. The nature of these predispositions is poorly understood, but is crucial to our understanding of how infants unpack their speech input to recover the fundamental word-like units, assign them referential roles, and acquire the rules that govern their organization. Previous researchers have demonstrated the role of general distributional computations in prelinguistic infants' parsing of continuous speech. We extend these findings to more naturalistic conditions, and find that 6-mo-old infants can simultaneously segment a nonce auditory word form from prosodically organized continuous speech and associate it to a visual referent. Crucially, however, this mapping occurs only when the word form is aligned with a prosodic phrase boundary. Our findings suggest that infants are predisposed very early in life to hypothesize that words are aligned with prosodic phrase boundaries, thus facilitating the word learning process. Further, and somewhat paradoxically, we observed successful learning in a more complex context than previously studied, suggesting that learning is enhanced when the language input is well matched to the learner's expectations.A cquiring a language includes learning mappings from sounds (or signs) to meanings. However, words-the principle units of meaning-are not given directly in the input, but are embedded in a speech signal whose structure is governed by grammatical processes operating at multiple levels. One of the primary steps in language acquisition, therefore, is to discover the sound sequences that define words. However, as any adult confronted with a foreign language can attest, it is hard to perceive unfamiliar speech as sequences of words. Additionally, the language learner must also discover what the words refer to, a particularly tricky problem given the innumerable possible referential features in the world (1, 2). Nevertheless, by 6 mo of age, infants have spontaneously extracted and begun to understand their first words, including highly frequent items such as "no", "Mommy", and the child's own name (3).Here we provide evidence that 6-mo-olds can rapidly extract a statistically defined, novel auditory word form from running speech and simultaneously map it onto a visual referent in an array of objects. Moreover, we find this dual process of word segmentation and referent mapping only when the statistically defined words are aligned with phrasal prosodic constituents, a universal structural property of natural languages. These findings build on three key results from past research: (i) 7-to 8-mo-old infants can extract statistically defined syllable sequences from fluent speech as candidate auditory word forms (4, 5), (ii) by 14 mo, infants can reliably map isolated auditory word forms onto visual referents (6-8), and (iii) by 17 mo, toddlers can extract auditory word forms on the basis of syllable statistics and subsequently map them onto candidate visual referents (9). We demonstrate all of these behaviors simulta...

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Section: (C-e) Speech Waveforms Pitch Tracks and Syllable Duratiosupporting

confidence: 81%

Prosody guides the rapid mapping of auditory word forms onto visual objects in 6-mo-old infants

Shukla

White

Aslin

2011

Proc. Natl. Acad. Sci. U.S.A.

182

157

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“…One possibility would be that learners should only acquire linguistic regularities that serve some functional or communicative purpose. The current experiments add to a body of artificial language learning experiments which show that this is not the case (Gomez, 2002;Mintz, 2002;Morgan, et al, 1987;Morgan & Newport, 1981;. Of course, in natural language the interplay between verb semantics and verb distribution is particularly rich and complex, and we know that this information plays a role in adult language (see Bresnan, Cueni, Tatiana, & Baayen, 2005, for a demonstration of the complex set of mutually constraining influencessemantic, pragmatic and phonological -affecting the production of the two dative constructions in English).…”

Section: Discussionmentioning

confidence: 90%

“…The benefits of using artificial languages as a means of obtaining precise control over the input to learning is now well established (Aslin, Saffran & Newport, 1998;Braine, 1963;Hudson Kam & Newport, 2005;Gerken, 2006;Gomez, 2002;Mintz, 2002;Moeser & Bregman, 1972;Morgan & Newport, 1981;Morgan, Meier & Newport, 1987;Wonnacott & Newport, 2005). In addition, there is emerging evidence that artificial languages exhibit many of the same signature results in processing as those obtained with natural language stimuli (e.g., Magnuson, Tanenhaus, Aslin & Dahan, 2003).…”

Section: The Current Workmentioning

confidence: 99%

“…Although most artificial language experiments have relied on grammaticality judgments (Braine 1990;Gomez, 2002;Moeser & Bregman, 1972;Morgan et al, 1987;Morgan & Newport, 1981;, some studies have also included tests of production and online comprehension (production: Hudson- Kam & Newport, 2005;Wonnacott & Newport, 2005;online comprehension: Magnuson et al, 2003). Including all three measures in the same experiments will allow us to compare different modes of learning.…”

Section: The Current Workmentioning

confidence: 99%

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Acquiring and processing verb argument structure: Distributional learning in a miniature language

Wonnacott

Newport

Tanenhaus

2008

Cognitive Psychology

193

216

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Adult knowledge of a language involves correctly balancing lexically-based and more languagegeneral patterns. For example, verb-argument structures may sometimes readily generalize to new verbs, yet with particular verbs may resist generalization. From the perspective of acquisition, this creates significant learnability problems (Baker 1979), with some researchers claiming a crucial role for verb semantics in the determination of when generalization may and may not occur (Pinker, 1989). Similarly, there has been debate regarding how verb-specific and more generalized constraints interact in sentence processing (Trueswell et al 1993;Mitchell 1987) and on the role of semantics in this process (Hare et al 2003). The current work explores these issues using artificial language learning. In three experiments using languages without semantic cues to verb distribution, we demonstrate that learners can acquire both verb-specific and verb-general patterns, based on distributional information in the linguistic input regarding each of the verbs as well as across the language as a whole. As with natural languages, these factors are shown to affect production, judgments and real-time processing. We demonstrate that learners apply a rational procedure in determining their usage of these different input-statistics and conclude by suggesting that a Bayesian perspective on statistical learning may be an appropriate framework for capturing our findings.

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“…In order to circumvent such problems, our studies combine insights and methodology from two lines of research: one examining infant learning of artificial language materials (Morgan and Saffran, 1995;Mintz, 1996;Saffran et al, 1996;Echols et al, 1997) and another involving studies of artificial grammar learning by adults (Reber, 1967(Reber, , 1969(Reber, , 1989Morgan and Newport, 1981;Morgan et al, 1987Morgan et al, , 1989Valian and Coulson, 1988;Valian and Levitt, 1996). The use of artificial language stimuli enables more precise control over the learning environment than is found using natural language.…”

Section: Introductionmentioning

confidence: 99%

Artificial grammar learning by 1-year-olds leads to specific and abstract knowledge

1999

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Four experiments used the head-turn preference procedure to assess whether infants could extract and remember information from auditory strings produced by a miniature artificial grammar. In all four experiments, infants generalized to new structure by discriminating new grammatical strings from ungrammatical ones after less than 2 min exposure to the grammar. Infants acquired specific information about the grammar as demonstrated by the ability to discriminate new grammatical strings from those with illegal endpoints (Experiment 1). Infants also discriminated new grammatical strings from those with string-internal pairwise violations (Experiments 2 and 3). Infants in Experiment 4 abstracted beyond specific word order as demonstrated by the ability to discriminate new strings produced by their training grammar from strings produced by another grammar despite a change in vocabulary between training and test. We discuss the implications of these findings for the study of language acquisition.

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Structural packaging in the input to language learning: Contributions of prosodic and morphological marking of phrases to the acquisition of language

Cited by 226 publications

References 38 publications

Prosody guides the rapid mapping of auditory word forms onto visual objects in 6-mo-old infants

Prosody guides the rapid mapping of auditory word forms onto visual objects in 6-mo-old infants

Acquiring and processing verb argument structure: Distributional learning in a miniature language

Artificial grammar learning by 1-year-olds leads to specific and abstract knowledge

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