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Language learners have to both segment words and discover grammatical rules connecting those words in sentences. In adult listeners, the presence of a prosodic cue in the speech stream, for example, a pause, appears to facilitate rule-learning of non-adjacent dependencies of the form AiXCi (Peña et al., 2002). Only when listening to the artificial language containing pauses, could participants identify rule-words of the form AiAjCi or AiCjCi, where intervening syllables were moved from A- or C-positions. Frost and Monaghan (2016) found in a similar study that participants who were tested with novel, rather than moved, intervening syllables in AiXCi items showed rule-learning even when the familiarisation stream contained no pauses. The present study re-examines the facilitative effect of pauses in discovering structural rules in speech in a novel population: children aged 7-11. We used the same artificial speech stimuli as Peña et al. (2002) and tested children in both a moved-syllable and novel-syllable forced-choice task. The results of 140 children show that pauses provide a facilitative effect on rule-learning – also for young learners. Regardless of syllable types, only children who listened to the familiarisation stream containing pauses chose words following the rule above chance-level.

Artificial grammar learning (AGL) has become an important tool used to understand aspects of human language learning and whether the abilities underlying learning may be unique to humans or found in other species. Successful learning is typically assumed when human or animal participants are able to distinguish stimuli generated by the grammar from those that are not at a level better than chance. However, the question remains as to what subjects actually learn in these experiments. Previous studies of AGL have frequently introduced multiple potential contributors to performance in the training and testing stimuli, but meta-analysis techniques now enable us to consider these multiple information sources for their contribution to learning-enabling intended and unintended structures to be assessed simultaneously. We present a blueprint for meta-analysis approaches to appraise the effect of learning in human and other animal studies for a series of artificial grammar learning experiments, focusing on studies that examine auditory and visual modalities. We identify a series of variables that differ across these studies, focusing on both structural and surface properties of the grammar, and characteristics of training and test regimes, and provide a first step in assessing the relative contribution of these design features of artificial grammars as well as species-specific effects for learning.

Achieving linguistic proficiency requires identifying words from speech, and discovering the constraints that govern the way those words are used. In a recent study of non-adjacent dependency learning, Frost and Monaghan (2016) demonstrated that learners may perform these tasks together, using similar statistical processes — contrary to prior suggestions. However, in their study, non-adjacent dependencies were marked by phonological cues (plosive- continuant-plosive structure), which may have influenced learning. Here, we test the necessity of these cues by comparing learning across three conditions; fixed phonology, which contains these cues, varied phonology, which omits them, and shapes, which uses visual shape sequences to assess the generality of statistical processing for these tasks. Participants segmented the sequences and generalized the structure in both auditory conditions, but learning was best when phonological cues were present. Learning was around chance on both tasks for the visual shapes group, indicating statistical processing may critically differ across domains

This dissertation addresses the question of whether non-adjacent morphological dependencies are as difficult to learn as non-adjacent phonological dependencies. Non-adjacent dependencies have been investigated in the past, and have proven to be at best difficult to learn (Bonatti, Peña, Nespor, & Mehler, 2005; Gómez, 2002; LaCross, 2011, 2015; Newport & Aslin, 2004), and at worst, completely unlearnable (Newport & Aslin, 2004: experiment 1). LaCross (2011, 2015) showed that speakers of a language employing non-adjacent dependencies were able to learn an artificial grammar employing analogous non-adjacent dependencies easily, suggesting there may be a linguistic bias that makes speakers more aware or capable of unconsciously parsing non-adjacent dependencies so long as they speak a language that employs vowel harmony. The research in this dissertation studies three subject populations with two tasks and two grammars to discover whether speakers of a language utilizing root-and-pattern morphology also have the ability to unconsciously parse non-adjacent dependencies pred- icated on morphological structure. Chapter 2 uses a segmentation or statistical learning task similar to the experiments mentioned above, while Chapter 3 uses a word elicitation task to establish a more fine-grained representation of what experiment participants learn after a very short exposure. The experiments show that there may be a cognitive bias toward concatenative morphology even among Arabic and Maltese speakers, but also that Arabic and Maltese speakers are willing to adjust CV skeleta and syllabic structure when deriving plural forms from singular forms. The methods that they use when producing novel plural forms are similar to those found in their L1, showing that this type of bias is predicated on morphophonological structure in the participants’ L1. The results together support a root-based lexicon for Arabic and Maltese and aggressive morphological decomposition (Boudelaa & Marslen-Wil

This dissertation explores the human ability for non-adjacent dependency-learning, which allows adults and infants to detect the relationship between a and b in an aXb string. I use artificial grammar learning with adults and infants to investigate whether non-adjacent dependency-learning could facilitate the detection of morpho-syntactic dependencies in natural languages (The princess is gently kissing the frog). Morpho-syntactic dependencies are typically instantiated between functional morphemes (is, -ing), straddling lexical morphemes (gently, kiss). Functional morphemes are often less prosodically prominent than lexical ones. I investigate the role that this prosodic contrast could play in non-adjacent dependency-learning: both adults and infants learn aXb dependencies when a/b are prosodically prominent, but also when they are prosodically weak compared to the intervening X, similar to functional morphemes straddling a lexical word. The prosodic properties of natural languages could thus facilitate non-adjacent dependency learning. Secondly, children seem to become familiar with the individual units of a morpho-syntactic dependency beforree learning the dependency itself. I investigate how prior familiarity with a/b impacts learning aXb dependencies for adults. Previous findings suggest a negative effect of prior familiarity with a/b, but I find that these results are based on a confound relating to the sequential presentation of two learning phases (learning a/bs, and learning aXb dependencies). Eliminating this confound, I find no significant disadvantage of prior familiarity with a/b. Finally, I show that adults can generalize a_b dependencies to novel aX’b strings (with unfamiliar X’), but, 18-month-olds show no such generalization. Young learners may only be able to track dependencies in familiar contexts.

This study examines novel language learning from inconsistent input in monolingual and bilingual toddlers. We predicted an advantage for the bilingual toddlers on the basis of the structural sensitivity hypothesis. Monolingual and bilingual 24‐month‐olds performed two novel language learning experiments. The first contained consistent input, and the second occasionally contained inconsistent input (i.e., 'errors'). Neither group showed learning of the novel pattern in the consistent experiment. The bilingual toddlers, but not the monolinguals, showed learning in the inconsistent experiment, which suggests they are better at detecting regularities from inconsistent input than monolinguals. Highlights Language learning experiments consider consistent input, whereas inconsistent input is likely to occur in real life. Monolingual and bilingual toddlers' performance on a language learning task of non‐adjacent dependencies was assessed, using inconsistent input. The group of bilingual toddlers was able to find the language pattern despite the inconsistencies, whereas the group of monolingual toddlers was not. (PsycINFO Database Record (c) 2016 APA, all rights reserved)

Many grammatical dependencies in natural language involve elements that are not adjacent, such as between the subject and verb in the child always runs. To date, most experiments showing evidence of learning non- adjacent dependencies have used artificial languages in which the to-be-learned dependencies are presented in isolation by presenting the minimal sequences that contain the dependent elements. However, dependencies in natural language are not typically isolated in this way. In this study we exposed learners to non-adjacent dependencies in long sequences of words. We accelerated the speed of presentation and learners showed evidence for learning of non-adjacent dependencies. The previous pause-based positional mechanisms for learning of non-adjacent dependency are challenged.

Although syntactic priming is well studied and commonly assumed to involve implicit learning, the mechanisms behind this phenomenon are still under debate. We tested whether implicit learning of adjacent and non-adjacent sequences occurs in a non-linguistic, finger sequence task (Serial Reaction Time task), and if so, whether these implicitly-learned dependencies can cause syntactic priming in the linguistic domain. We followed the logic that exposure to statistical patterns in the SRT task may influence language users’ relative clause (RC) attachment biases, and trained participants on SRT sequences with adjacent or non-adjacent dependencies. Participants then wrote completions to relative clause fragments in a situation where they could opt for adjacent or non-adjacent linguistic structures. Participants successfully learned the adjacent and non-adjacent dependency implicitly during the SRT task, but, strikingly, their RC continuations did not exhibit priming effects. Implications for theories of syntactic priming and its relations to implicit learning are discussed.

Many studies of human sequential pattern learning demonstrate that learners detect adjacent and non-adjacent dependencies in many kinds of sequences. However, it is often assumed that the computational mechanisms behind extracting these dependencies are the same. We replicate the seminal finding that adults are capable of learning dependencies between non-adjacent words (Gómez, 2002). When we eliminate the positional information about the statistical structures by embedding the structure in phrases, learners can no longer learn the dependencies. Our methods allow us to study the learning mechanisms that are more representative of the patterns in natural languages, and show that when directly compared, adjacent and non-adjacent dependencies are not equally learnable. We suggest that learning non-adjacent dependencies in language involves a different computational mechanism from learning adjacent dependencies

The phenomenon of syntactic priming is well studied in the literature, but the mechanisms behind it are still under debate. In this study, we trained English-speaking participants in artificial language sequences with dependencies that are either adjacent or non-adjacent. The participants then wrote completions to relative clause (RC) fragments. We found that participants who learn non-adjacent dependencies in the artificial language, exhibit a bias to write high-attachment (non-adjacent) continuations for RCs, when compared to participants in a control condition who exhibit low-attachment (adjacent) biases in RCs. The implications for theories of syntactic priming and its relations to implicit learning are discussed.

Previous research on speakers' abilities to track non-adjacent dependencies (e.g., vowels or consonants that co-occur across syllables) in artificial grammar learning (AGL) tasks has shown that the acquisition of these patterns is extremely difficult (e.g. Newport&Aslin 2004; Gómez 2002; Bonatti, PenÞa, Nespor&Mehler 2005). One assumption made in this literature is that all speakers of all languages should be capable of tracking these patterns even when the native language of those speakers contains no such non-adjacent dependencies. This dissertation questions this assumption by testing whether native Khalkha Mongolian speakers attend to and track the frequency of vowel patterns and harmonic class size in their language. It also tests their ability to acquire non-adjacent vocalic dependencies in AGL tasks.Because Khalkha displays [ATR] vowel harmony (Svantesson, Tsendina, Karlsson&Franzén 2005) which restricts vowel co-occurrences, it was hypothesized that Khalkha speakers are biased towards attending to the frequency and form with which these vowel patterns occur. The results of three experiments indicated that Khalkha speakers both attend to and track the frequency with which vowel patterns occur. These results also indicate that Khalkha speakers build abstract categories based on the relative token numbers of [+ATR] and [-ATR]harmonic spans.Khalkha speakers were further tested in three experiments which focused on speakers' ability to acquire novel non-adjacent vocalic dependencies in AGL tasks. The results indicated that participants successfully acquired vocalic dependencies (both harmonic and disharmonic) in all three experiments. These results indicate that Khalkha speakers' attention is biased towards vowels, regardless of harmonic status of the item.Collectively, these results highlight the role of language-specific phonology in the ways that speakers abstract and utilize phonological information. The special status of harmonic vowel patterns and harmonic