“Frequent Frames” in German Child-Directed Speech: A Limited Cue to Grammatical Categories

Abstract

Mintz (2003) found that in English child-directed speech, frequently occurring frames formed by linking the preceding (A) and succeeding (B) word (A_x_B) could accurately predict the syntactic category of the intervening word (x). This has been successfully extended to French (Chemla, Mintz, Bernal, & Christophe, 2009). In this paper, we show that, as for Dutch (Erkelens, 2009), frequent frames in German do not enable such accurate lexical categorization. This can be explained by the characteristics of German including a less restricted word order compared to English or French and the frequent use of some forms as both determiner and pronoun in colloquial German. Finally, we explore the relationship between the accuracy of frames and their potential utility and find that even some of those frames showing high token-based accuracy are of limited value because they are in fact set phrases with little or no variability in the slot position.

Word categorization from distributional information: Frames confer more than the sum of their (Bigram) parts

“…This is because words in English that are immediately surrounded by you and it are almost exclusively verbs. While other studies have presented similar evidence (Mintz, 2002; Reeder, Newport, & Aslin, 2013), our findings are significant because they demonstrate that learners are especially responsive to a particular type of distributional pattern called a frequent frame (like the English you_it frame just mentioned), which has been shown computationally to be an especially accurate source of grammatical category information cross-linguistically (Chemla, Mintz, Bernal, & Christophe, 2009; Erkelens, 2009; Stumper, Bannard, Lieven, & Tomasello, 2011; Wang, Hohle, Ketrez, Kuntay, & Mintz, 2011; Weisleder & Waxman, 2010). Our study thus sheds light on the particular kinds of distributional patterns to which human learners attend, and their potential relevance in human language acquisition.…”

“…It is unknown, however, what the source of that distributional knowledge was. Since French and German both have informative frequent frames at the lexical or morphological level (Chemla et al, 2009; Stumper et al, 2011; Wang et al, 2011), one possibility is that infants used frames to carry out initial categorization and observed that the functors in question were highly diagnostic of the frame-based categories, and thus started to use them as additional distributional contexts (Wang et al, 2011). It is also possible that when frequency differences between words within bigrams are much greater than in our materials—the relative frequency of function words to content words in natural languages are generally much greater than in most artificial languages—learners start using very frequent words as generalization contexts for adjacent words, without first processing the frames in which they occur.…”

“…Researchers have found similar patterns in French (Chemla et al, 2009) and Spanish (Weisleder & Waxman, 2010). That said, the category information provided by frequent lexical frames in child-directed German—a language that has more variable word order—is not as robust as in those other languages (Stumper et al, 2011; Wang et al, 2011). This result could be taken as evidence that frequent frames, and perhaps distributional information in general, may be less useful for languages with freer word order.…”

The ubiquity of frequency effects in first language acquisition

“…Similar findings were observed by Matthews and Bannard ( 2010 ), Arnon and Snider ( 2010 ), and Arnon and Clark ( 2011 ; see also Conklin & Schmitt, 2012 , for an overview of such effects in adults). In a different context, a number of studies (Mintz, 2003 ; Chemla, Mintz, Bernal, and Christophe, 2009 ; Weisleder & Waxman, 2010; but see Erkelens, 2009 ; Stumper, Bannard, Lieven & Tomasello, 2011 ) have demonstrated that children are also sensitive to frequent frames: “ordered pairs of words that frequently co-occur with exactly one word position intervening (occupied by any word)” (Mintz, 2003 , p. 93).…”

All Together Now: Concurrent Learning of Multiple Structures in an Artificial Language

“…Additionally, because X is likely to be a verb, there is an adjacent regularity between was and X (i.e., the conditional probability of run given was is higher than that of cat given was ). The usefulness of frequent frames as a cue to lexical categories depends on the distributional properties of the language, and frequent frames are not equally useful for all natural languages (Stumper, Bannard, Lieven, & Tomasello, ; see also St. Clair, Monaghan, & Christiansen, for discussion).…”