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Statistical Language Learning: Learning-Oriented Theories Is That Mechanisms and Constraints Such Accounts Seem at Odds with One of the Central Observations 1 Jenny R

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Statistical Language Learning: Learning-Oriented Theories Is That Mechanisms and Constraints Such Accounts Seem at Odds with One of the Central Observations 1 Jenny R 110 VOLUME 12, NUMBER 4, AUGUST 2003 most important arguments against Statistical Language Learning: learning-oriented theories is that Mechanisms and Constraints such accounts seem at odds with one of the central observations 1 Jenny R. Saffran about human languages. The lin- Department of Psychology and Waisman Center, University of Wisconsin–Madison, guistic systems of the world, de- Madison, Wisconsin spite surface differences, share deep similarities, and vary in non- arbitrary ways. Theories of language Abstract guage, it seems improbable that chil- acquisition that focus primarily on What types of mechanisms dren could ever discern its structure. preexisting knowledge of language underlie the acquisition of hu- The process of acquiring such a sys- do provide an elegant explanation man language? Recent evidence tem is likely to be nearly as com- for cross-linguistic similarities. suggests that learners, includ- plex as the system itself, so it is not Such theories, which are exempli- ing infants, can use statistical surprising that the mechanisms un- fied by the seminal work of Noam properties of linguistic input to derlying language acquisition are a Chomsky, suggest that linguistic uni- discover structure, including matter of long-standing debate. One versals are prespecified in the child’s sound patterns, words, and the of the central focuses of this debate linguistic endowment, and do not re- beginnings of grammar. These concerns the innate and environ- quire learning. Such accounts gener- abilities appear to be both pow- mental contributions to the lan- ate predictions about the types of erful and constrained, such that guage-acquisition process, and the patterns that should be observed some statistical patterns are degree to which these components cross-linguistically, and lead to im- more readily detected and used draw on information and abilities portant claims regarding the evolu- than others. Implications for the that are also relevant to other do- tion of a language capacity that in- structure of human languages mains of learning. cludes innate knowledge of this kind are discussed. In particular, there is a funda- (e.g., Pinker & Bloom, 1990). mental tension between theories of Can learning-oriented theories language acquisition in which also account for the existence of Keywords learning plays a central role and language universals? The answer to language acquisition; statistical theories in which learning is rele- this question is the object of current learning; infants gated to the sidelines. A strength research. The constrained statistical of learning-oriented theories is that learning framework suggests that they exploit the growing wealth of learning is central to language acqui- Imagine that you are faced with evidence suggesting that young sition, and that the specific nature of the following challenge: You must humans possess powerful learning language learning explains similar- discover the underlying structure mechanisms. For example, infants ities across languages. The crucial of an immense system that contains can rapidly capitalize on the statis- point is that learning is constrained; tens of thousands of pieces, all gen- tical properties of their language learners are not open-minded, and erated by combining a small set of environments, including the distri- calculate some statistics more elements in various ways. These butions of sounds in words and the readily than others. Of particular in- pieces, in turn, can be combined in orders of word types in sentences, terest are those constraints on learn- an infinite number of ways, although to discover important components ing that correspond to cross-linguis- only a subset of those combinations of language structure. Infants can tic similarities (e.g., Newport & is actually correct. However, the sub- track such statistics, for example, Aslin, 2000). According to this set that is correct is itself infinite. to discover speech categories (e.g., framework, the similarities across Somehow you must rapidly figure native-language consonants; see, e.g., languages are indeed nonacciden- out the structure of this system so Maye, Werker, & Gerken, 2002), tal, as suggested by the Chomskian that you can use it appropriately word boundaries (e.g., Saffran, Aslin, framework—but they are not the early in your childhood. & Newport, 1996), and rudimentary result of innate linguistic knowl- This system, of course, is human syntax (e.g., Gomez & Gerken, edge. Instead, human languages language. The elements are the 1999; Saffran & Wilson, 2003). have been shaped by human learn- sounds of language, and the larger However, theories of language ing mechanisms (along with con- pieces are the words, which in turn acquisition in which learning plays straints on human perception, pro- combine to form sentences. Given a central role are vulnerable to a cessing, and speech production), and the richness and complexity of lan- number of criticisms. One of the aspects of language that enhance Published by Blackwell Publishing Inc. CURRENT DIRECTIONS IN PSYCHOLOGICAL SCIENCE 111 learnability are more likely to per- is a challenging problem for infants words, we exposed adults, first sist in linguistic structure than acquiring their first language, for graders, and 8-month-olds to spo- those that do not. Thus, according speakers do not mark word bound- ken nonsense languages in which to this view, the similarities across aries with pauses, as shown in Fig- the only cues to word boundaries languages are not due to innate ure 1. Instead, infants must deter- were the statistical properties of knowledge, as is traditionally mine where one word ends and the the syllable sequences (e.g., Saffran claimed, but rather are the result of next begins without access to obvi- et al., 1996). Listeners briefly heard constraints on learning. Further, if ous acoustic cues. This process re- a continuous sequence of syllables human languages were (and con- quires learning because children containing multisyllabic words tinue to be) shaped by constraints cannot innately know that, for exam- from one of the languages (e.g., on human learning mechanisms, it ple, pretty and baby are words, golabupabikututibubabupugola- seems likely that these mechanisms whereas tyba (spanning the bound- bubabupu. ). We then tested our and their constraints were not tai- ary between pretty and baby) is not. participants to determine whether lored solely for language acquisi- One source of information that they could discriminate the words tion. Instead, learning in nonlinguis- may contribute to the discovery of from the language from sequences tic domains should be similarly word boundaries is the statistical spanning word boundaries. For ex- constrained, as seems to be the structure of the language in the in- ample, we compared performance case. fant’s environment. In English, the on words like golabu and pabiku A better understanding of these syllable pre precedes a small set of with performance on sequences like constraints may lead to new con- syllables, including ty, tend, and cedes; bupabi, which spanned the bound- nections between theories focused in the stream of speech, the probabil- ary between words. To succeed at on nature and theories focused on ity that pre is followed by ty is thus this task, listeners would have had nurture. Constrained learning mech- quite high (roughly 80% in speech to track the statistical properties of anisms require both particular expe- to young infants). However, because the input. Our results confirmed that riences to drive learning and pre- the syllable ty occurs word finally, it human learners, including infants, existing structures to capture and can be followed by any syllable that can indeed use statistics to find manipulate those experiences. can begin an English word. Thus, word boundaries. Moreover, this the probability that ty is followed ability is not confined to humans: by ba, as in pretty baby, is extremely Cotton-top tamarins, a New World low (roughly 0.03% in speech to monkey species, can also track sta- LEARNING THE SOUNDS young infants). This difference in se- tistics to discover word boundaries OF WORDS quential probabilities is a clue that (Hauser, Newport, & Aslin, 2001). pretty is a word, and tyba is not. One question immediately raised In order to investigate the nature More generally, given the statistical by these results is the degree to of infants’ learning mechanisms, my properties of the input language, which statistical learning is limited colleagues and I began by studying the ability to track sequential prob- to languagelike stimuli. A growing an aspect of language that we knew abilities would be an extremely body of results suggests that se- must certainly be learned: word useful tool for infant learners. quential statistical learning is quite segmentation, or the boundaries be- To explore whether humans can general. For example, infants can tween words in fluent speech. This use statistical learning to segment track sequences of tones, discovering “tone-word boundaries” via statisti- cal cues (e.g., Saffran, Johnson, As- lin, & Newport, 1999), and can learn statistically defined visual patterns (e.g., Fiser & Aslin, 2002; Kirkham, Slemmer, & Johnson, 2002); work in progress is extending these re- sults to the domain of events in hu- man action sequences. Given that the ability to discover Fig. 1. A speech waveform of the sentence “Where are the silences between words?” units via their statistical coherence The height of the bars indicates loudness,
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