Processing Function Words in Artificial Languages: Effects of Function Word Presence and Perceptual Cues

Processing Function Words in Artificial Languages: Effects of Function Word Presence and Perceptual Cues Dan Hufnagle (dghufnag@ucalgary.ca) Department of Psychology, 2500 University Drive NW Calgary, AB T2N 1N4 Canada Suzanne Curtin (scurtin@ucalgary.ca) Departments of Psychology and Linguistics, 2500 University Drive NW Calgary, AB T2N 1N4 Canada Abstract Language learners use function words as indicators of structure. Across languages, function and content differ phonologically and acoustically, and learners may use these cues to help organize an emerging lexicon into categories. We tested three versions of an artificial language: no differences between function and non-function words, reduced vowels for function words, and no onsets for function words. Counter to expectations, learners of the language with no cues to category membership performed best on grammaticality judgments. At test, the presence of function words was also manipulated. There is an interaction between presence of function words in test sentences and the type of pattern being tested, indicating that function words help learners process some patterns, but are detrimental for others. Keywords: Artificial language learning; function words; syntax acquisition. Introduction Function words and morphemes have a number of characteristics that make them special in language. They serve as the scaffold around which the meaning in a sentence is built. They organize sentences, providing structure within phrases as well as connections among phrases. Function words are a closed class: new function words rarely enter a language and constitute a small part of the lexicon relative to non-function words. Despite their low type frequency, function words have high token frequency. Experiments using artificial languages have explored the role of function words in acquisition. Learners can form categories quite rapidly by calculating distributions of co- occurrences (Mintz, 2002) and can use those distributions to determine which elements are predictive of other elements (Saffran, 2001). When predictive elements in artificial languages act to reliably signal whole classes of other elements that occur in the language, they become analogous to function words in natural language. Thus, when learners have access to distributional information about co- occurrence, learners can induce categories in artificial languages that play the role of function words, even when words in those languages are not tied to meaning. Artificial languages that include function words are learned better than languages that do not include predictive elements or languages with similar elements that are not predictive (Green, 1979). This advantage for predictive elements only holds when the relative frequency of predictive to non-predictive elements is high (Valian & Coulson, 1988): learners of an artificial language with a low ratio of function words to non-function word (mimicking natural language) learned the language faster and at a deeper level than learners who learned a language with a higher ratio of function to non-function words. Whether or not function words are optional also affects acquisition. Hudson Kam and Newport (2005) exposed learners to a simple, meaning-based artificial language and used a number of tasks to measure the effects of the proportion of exposure sentences that contained function words. While the researchers framed the experiment in terms of regularizing patterns from inconsistent input (i.e., creolization), their experiments also show how people differ in learning languages with required versus optional function words if the input is taken as faithful to the target language. Adults’ productions and sentence ratings mirrored the function word characteristics of the input language: when function words were presented in all contexts (i.e., required by the language), learners recognized the requirement. When function words were variable in the input, learners recognized the optionality, either dropping them altogether or used them variably. Clearly people can use function words, even when those words compete with meaningful words for cognitive resources. Together, this research underscores the importance of the distributional properties of function words in the acquisition of language. Another question involves the use of function words in processing the grammatical structure of sentences. In a language with optional function words, does their presence in a given sentence help or hinder processing? Our hypothesis is that because function words act as markers of structure, sentences with more function words will be easier to process than sentences with fewer function words. In order to test this hypothesis, we varied the presence and absence of function words within the test phase for each language in the experiment. If function words act as syntactic anchors, and people are able to learn which words of the grammar are function words, then ungrammatical sentences should be easier to detect in the trials that make greater use of function words, leading to higher scores on a grammaticality judgment task.