Toben H. Mintz

Frequent Frames as a Cue for Grammatical Categories in Child Directed Speech.

This paper introduces the notion of frequent frames, distributional patterns based on co-occurrence patterns of words in sentences, then investigates the usefulness of this information in grammatical categorization. A frame is defined as two jointly occurring words with one word intervening. Qualitative and quantitative results from distributional analyses of six different corpora of child directed speech are presented in two experiments. In the analyses, words that were surrounded by the same frequent frame were categorized together. The results show that frequent frames yield very accurate categories. Furthermore, evidence from behavioral studies suggests that infants and adults are sensitive to frame-like units, and that adults use them to categorize words. This evidence, along with the success of frames in categorizing words, provides support for frames as a basis for the acquisition of grammatical categories.

Category induction from distributional cues in an artificial language

The ability to identify the grammatical category of a word (e.g., noun, verb, adjective) is a fundamental aspect of competence in a natural language. Children show evidence of categorization by as early as 18 months, and in some cases younger. However, the mechanisms that underlie this ability are not well understood. The lexical co-occurrence patterns of words in sentences could provide information about word categories—for example, words that followthe in English often belong to the same category. As a step in understanding the role distributional mechanisms might play in language learning, the present study investigated the ability of adults to categorize words on the basis of distributional information. Forty participants listened for approximately 6 min to sentences in an artificial language and were told that they would later be tested on their memory for what they had heard. Participants were next tested on an additional set of sentences and asked to report which sentences they recognized from the first 6 min. The results suggested that learners performed a distributional analysis on the initial set of sentences and recognized sentences on the basis of their memory of sequences ofcategories of words. Thus, mechanisms that would be useful in natural language learning were shown to be active in adults in an artificial language learning task.

Categorizing words using ‘frequent frames’: what cross-linguistic analyses reveal about distributional acquisition strategies

Mintz (2003) described a distributional environment called a frame, defined as the co-occurrence of two context words with one intervening target word. Analyses of English child-directed speech showed that words that fell within any frequently occurring frame consistently belonged to the same grammatical category (e.g. noun, verb, adjective, etc.). In this paper, we first generalize this result to French, a language in which the function word system allows patterns that are potentially detrimental to a frame-based analysis procedure. Second, we show that the discontinuity of the chosen environments (i.e. the fact that target words are framed by the context words) is crucial for the mechanism to be efficient. This property might be relevant for any computational approach to grammatical categorization. Finally, we investigate a recursive application of the procedure and observe that the categorization is paradoxically worse when context elements are categories rather than actual lexical items. Item-specificity is thus also a core computational principle for this type of algorithm. Our analysis, along with results from behavioural studies (Gómez, 2002; Gómez and Maye, 2005; Mintz, 2006), provides strong support for frames as a basis for the acquisition of grammatical categories by infants. Discontinuity and item-specificity appear to be crucial features.

Word Categorization From Distributional Information: Frames Confer More Than the Sum of Their (Bigram) Parts

Grammatical categories, such as noun and verb, are the building blocks of syntactic structure and the components that govern the grammatical patterns of language. However, in many languages words are not explicitly marked with their category information, hence a critical part of acquiring a language is categorizing the words. Computational analyses of child-directed speech have shown that distributional information-information about how words pattern with one another in sentences-could be a useful source of initial category information. Yet questions remain as to whether learners use this kind of information, and if so, what kinds of distributional patterns facilitate categorization. In this paper we investigated how adults exposed to an artificial language use distributional information to categorize words. We compared training situations in which target words occurred in frames (i.e., surrounded by two words that frequently co-occur) against situations in which target words occurred in simpler bigram contexts (where an immediately adjacent word provides the context for categorization). We found that learners categorized words together when they occurred in similar frame contexts, but not when they occurred in similar bigram contexts. These findings are particularly relevant because they accord with computational investigations showing that frame contexts provide accurate category information cross-linguistically. We discuss these findings in the context of prior research on distribution-based categorization and the broader implications for the role of distributional categorization in language acquisition.

The Segmentation of Sub-Lexical Morphemes in English-Learning 15-Month-Olds

In most human languages, important components of linguistic structure are carried by affixes, also called bound morphemes. The affixes in a language comprise a relatively small but frequently occurring set of forms that surface as parts of words, but never occur without a stem. They combine productively with word stems and other grammatical entities in systematic and predictable ways. For example, the English suffix -ing occurs on verb stems, and in combination with a form of the auxiliary verb be, marks the verb with progressive aspect (e.g., was walking). In acquiring a language, learners must acquire rules of combination for affixes. However, prior to learning these combinatorial rules, learners are faced with discovering what the sub-lexical forms are over which the rules operate. That is, they have to discover the bound morphemes themselves. It is not known when English-learners begin to analyze words into morphological units. Previous research with learners of English found evidence that 18-month-olds have started to learn the combinatorial rules involving bound morphemes, and that 15-month-olds have not. However, it is not known whether 15-month-olds nevertheless represent the morphemes as distinct entities. This present study demonstrates that when 15-month-olds process words that end in -ing, they segment the suffix from the word, but they do not do so with endings that are not morphemes. Eight-month olds do not show this capacity. Thus, 15-month-olds have already started to identify bound morphemes and actively use them in processing speech.

Greater sensitivity to nonaccidental than metric shape properties in preschool children.

Nonaccidental properties (NAPs) are image properties that are invariant over orientation in depth and allow facile recognition of objects at varied orientations. NAPs are distinguished from metric properties (MPs) that generally vary continuously with changes in orientation in depth. While a number of studies have demonstrated greater sensitivity to NAPs in human adults, pigeons, and macaque IT cells, the few studies that investigated sensitivities in preschool children did not find significantly greater sensitivity to NAPs. However, these studies did not provide a principled measure of the physical image differences for the MP and NAP variations. We assessed sensitivity to NAP vs. MP differences in a nonmatch-to-sample task in which 14 preschool children were instructed to choose which of two shapes was different from a sample shape in a triangular display. Importantly, we scaled the shape differences so that MP and NAP differences were roughly equal (although the MP differences were slightly larger), using the Gabor-Jet model of V1 similarity (Lades & et al., 1993). Mean reaction times (RTs) for every child were shorter when the target shape differed from the sample in a NAP than an MP. The results suggest that preschoolers, like adults, are more sensitive to NAPs, which could explain their ability to rapidly learn new objects, even without observing them from every possible orientation.

Can You Believe It? 12-Month-Olds Use Word Order to Distinguish between Declaratives and Polar Interrogatives.

Word order is a core mechanism for conveying syntactic structure, yet interrogatives usually disrupt canonical word orders. For example, in English, polar interrogatives typically invert the subject and auxiliary verb and insert an utterance-initial do if no auxiliary is present. These word order patterns result from differences in the underlying syntactic structures; therefore, distinguishing interrogatives from declaratives is crucial for learning the syntax of interrogatives. More broadly, the ability to differentiate sentence types is critical for avoiding errors in syntax acquisition that would occur if interrogatives and declaratives were evaluated as the same type of utterance. Despite the importance of this issue, little is known about when and how infants begin to differentiate sentence types. In this study we exposed one group of 12-month-old infants to auditory passages of polar interrogatives and another group to passages of declaratives. To test sentence discrimination, infants in both groups were played new sets of declaratives and interrogatives in a procedure in which infants controlled how long they listened to each set. The sentences were acoustically modified to remove all prosodic cues that could differentiate them. Regardless of group, infants listened longer to the type of sentence that was different from the type to which they were initially exposed, indicating that they differentiated the sentence types based on lexical distributional patterns. We thus established that, despite only just beginning to produce single word utterances, 12-month-olds are sensitive to word-order properties that differentiate declaratives from interrogatives.

Learning Nonadjacent Dependencies Embedded in Sentences of an Artificial Language: When Learning Breaks Down.

The structure of natural languages give rise to many dependencies in the linear sequences of words, and within words themselves. Detecting these dependencies is arguably critical for young children in learning the underlying structure of their language. There is considerable evidence that human adults and infants are sensitive to the statistical properties of sequentially adjacent items. However, the conditions under which learners detect nonadjacent dependencies (NADs) appears to be much more limited. This has resulted in proposals that the kinds of learning mechanisms learners deploy in processing adjacent dependencies are fundamentally different from those deployed in learning NADs. Here we challenge this view. In 4 experiments, we show that learning both kinds of dependencies is hindered in conditions when they are embedded in longer sequences of words, and facilitated when they are isolated by silences. We argue that the findings from the present study and prior research is consistent with a theory that similar mechanisms are deployed for adjacent and nonadjacent dependency learning, but that NAD learning is simply computationally more complex. Hence, in some situations NAD learning is only successful when constraining information is provided, but critically, that additional information benefits adjacent dependency learning in similar ways.

Top-down structure influences learning of nonadjacent dependencies in an artificial language.

Because of the hierarchical organization of natural languages, words that are syntactically related are not always linearly adjacent. For example, the subject and verb in the child always runs agree in person and number, although they are not adjacent in the sequences of words. Since such dependencies are indicative of abstract linguist structure, it is of significant theoretical interest how these relationships are acquired by language learners. Most experiments that investigate nonadjacent dependency (NAD) learning have used artificial languages in which the to-be-learned dependencies are isolated, by presenting the minimal sequences that contain the dependent elements. However, dependencies in natural language are not typically isolated in this way. We report the first demonstration to our knowledge of successful learning of embedded NADs, in which silences do not mark dependency boundaries. Subjects heard passages of English with a predictable structure, interspersed with passages of the artificial language. The English sentences were designed to induce boundaries in the artificial languages. In Experiment 1 & 3 the artificial NADs were contained within the induced boundaries and subjects learned them, whereas in Experiment 2 & 4, the NADs crossed the induced boundaries and subjects did not learn them. We take this as evidence that sentential structure was “carried over” from the English sentences and used to organize the artificial language. This approach provides several new insights into the basic mechanisms of NAD learning in particular and statistical learning in general.

Prosodic Differences between Declaratives and Interrogatives in Infant-Directed Speech.

In many languages, declaratives and interrogatives differ in word order properties, and in syntactic organization more broadly. Thus, in order to learn the distinct syntactic properties of the two sentence types, learners must first be able to distinguish them using non-syntactic information. Prosodic information is often assumed to be a useful basis for this type of discrimination, although no systematic studies of the prosodic cues available to infants have been reported. Analysis of maternal speech in three Standard American English-speaking mother-infant dyads found that polar interrogatives differed from declaratives on the patterning of pitch and duration on the final two syllables, but wh-questions did not. Thus, while prosody is unlikely to aid discrimination of declaratives from wh-questions, infant-directed speech provides prosodic information that infants could use to distinguish declaratives and polar interrogatives. We discuss how learners could leverage this information to identify all question forms, in the context of syntax acquisition.