Processing multiple non-adjacent dependencies: evidence from sequence learning

Abstract

Processing non-adjacent dependencies is considered to be one of the hallmarks of human language. Assuming that sequence-learning tasks provide a useful way to tap natural-language-processing mechanisms, we cross-modally combined serial reaction time and artificial-grammar learning paradigms to investigate the processing of multiple nested (A 1 A 2 A 3 B 3 B 2 B 1 ) and crossed dependencies (A 1 A 2 A 3 B 1 B 2 B 3 ), containing either three or two dependencies. Both reaction times and prediction errors highlighted problems with processing the middle dependency in nested structures (A 1 A 2 A 3 B 3 _B 1 ), reminiscent of the 'missing-verb effect' observed in English and French, but not with crossed structures (A 1 A 2 A 3 B 1 _B 3 ). Prior linguistic experience did not play a major role: native speakers of German and Dutch-which permit nested and crossed dependencies, respectively-showed a similar pattern of results for sequences with three dependencies. As for sequences with two dependencies, reaction times and prediction errors were similar for both nested and crossed dependencies. The results suggest that constraints on the processing of multiple non-adjacent dependencies are determined by the specific ordering of the non-adjacent dependencies (i.e. nested or crossed), as well as the number of non-adjacent dependencies to be resolved (i.e. two or three). Furthermore, these constraints may not be specific to language but instead derive from limitations on structured sequence learning.Keywords: non-adjacent dependencies; sequence learning; artificial grammar learning; serial reaction time THEORETICAL BACKGROUNDThe natural-language phenomenon of recursion and its potential underlying processing mechanisms have attracted great interest from scholars of different fields, including psycholinguistics, biology, computer science and cognitive neuroscience. Most research so far has focused on sequence-learning tasks, assuming that they share cognitive mechanisms with language processing. The focus in the past decade was to determine whether such tasks could capture processing differences between specific language structures, often with their processing complexity defined in terms of the Chomsky hierarchy [1]. In the current paper, we identify two different sources of processing complexity, and we propose that processing differences are intrinsically tied to (i) the memory resources required and (ii) relevant processing experience [2]. We will empirically investigate this claim by focusing on non-adjacent dependency processing.(a) Non-adjacency in language Recursion has been suggested to be a hallmark of human language (cf.[3]). Recursion is an operation that permits a finite set of rules to generate an infinite number of expressions. In this paper, we concentrate on bounded recursive structures involving multiple overlapping non-adjacent dependencies. Their existence has been suggested by generative linguists to be one of the major challenges for empirically based approaches to language [4], as they may point to the lim...

How hierarchical is language use?

“…Consequently, such sentences are harder to understand [43], and possibly harder to learn [44], than sentences with crossed dependencies, as in (7). These effects have been replicated in a study employing a cross-modal serial-reaction time (SRT) task [45], suggesting that processing differences between crossed and nested dependencies derive from constraints on sequential learning abilities. Additionally, the Dutch/ German results have been simulated by recurrent neural network (RNN) models [46,47] that are fundamentally sequential in nature.…”

“…Presumably, this is because of the large linear distance between the early nouns and the late verbs, which makes it hard to keep all nouns in memory [48]. Results from SRT learning [45], providing a sequence-based analogue of this effect, show that the processing problem indeed derives from sequence-memory limitations and not from referential difficulties. Interestingly, the reading-time effect did not occur in comparable German sentences, possibly because German speakers are more often exposed to sentences with clause-final verbs [49].…”

Scarcity of crossing dependencies: A direct outcome of a specific constraint?

“…If the model is interpreted as arising from processing difficulties inherent to crossing dependencies [41] or computational tractability (as reviewed in Section I) then it is challenged by psychological and graph theoretic research indicating that sentences with C > 0 can be easier to process than sentences with C = 0 (see [48], [27], [58] and references therein). Another problem is how a language generation process could warrant that C = 0.…”

Pattern perception and computational complexity: introduction to the special issue

“…This issue is explored in detail by Fitch & Friederici [63] and Petersson & Hagoort [69]. Another concerns the degree to which formal 'competence' models can be reconciled with performance models [70]. Finally, the fraught issue of what, if anything, this whole line of research has to do with 'recursion' is covered by the contributions from Martins [71] and from Poletiek & Lai [72].…”