Padraic Monaghan

Eye-fixation behavior, lexical storage, and visual word recognition in a split processing model.

Some of the implications of a model of visual word recognition in which processing is conditioned by the anatomical splitting of the visual field between the two hemispheres of the brain are explored. The authors investigate the optimal processing of visually presented words within such an architecture, and, for a realistically sized lexicon of English, characterize a computationally optimal fixation point in reading. They demonstrate that this approach motivates a range of behavior observed in reading isolated words and text, including the optimal viewing position and its relationship with the preferred viewing location, the failure to fixate smaller words, asymmetries in hemisphere-specific processing, and the priority given to the exterior letters of words. The authors also show that split architectures facilitate the uptake of all the letter-position information necessary for efficient word recognition and that this information may be less specific than is normally assumed. A split model of word recognition captures a range of behavior in reading that is greater than that covered by existing models of visual word recognition.

Phonological typicality influences on-line sentence comprehension

Since Saussure, the relationship between the sound and the meaning of words has been regarded as largely arbitrary. Here, however, we show that a probabilistic relationship exists between the sound of a word and its lexical category. Corpus analyses of nouns and verbs indicate that the phonological properties of the individual words in these two lexical categories form relatively separate and coherent clusters, with some nouns sounding more typical of the noun category than others and likewise for verbs. Additional analyses reveal that the phonological properties of nouns and verbs affect lexical access, and we also demonstrate the influence of such properties during the on-line processing of both simple unambiguous and syntactically ambiguous sentences. Thus, although the sound of a word may not provide cues to its specific meaning, phonological typicality, the degree to which the sound properties of an individual word are typical of other words in its lexical category, affects both word- and sentence-level language processing. The findings are consistent with a perspective on language comprehension in which sensitivity to multiple syntactic constraints in adulthood emerges as a product of language-development processes that are driven by the integration of multiple cues to linguistic structure, including phonological typicality.

The Phonological-Distributional Coherence Hypothesis: Cross-Linguistic Evidence in Language Acquisition.

Several phonological and prosodic properties of words have been shown to relate to differences between grammatical categories. Distributional information about grammatical categories is also a rich source in the childs language environment. In this paper we hypothesise that such cues operate in tandem for developing the childs knowledge about grammatical categories. We term this the Phonological-Distributional Coherence Hypothesis (PDCH). We tested the PDCH by analysing phonological and distributional information in distinguishing open from closed class words and nouns from verbs in four languages: English, Dutch, French, and Japanese. We found an interaction between phonological and distributional cues for all four languages indicating that when distributional cues were less reliable, phonological cues were stronger. This provides converging evidence that language is structured such that language learning benefits from the integration of information about category from contextual and sound-based sources, and that the childs language environment is less impoverished than we might suspect.

Arbitrariness, iconicity, and systematicity in language

The notion that the form of a word bears an arbitrary relation to its meaning accounts only partly for the attested relations between form and meaning in the languages of the world. Recent research suggests a more textured view of vocabulary structure, in which arbitrariness is complemented by iconicity (aspects of form resemble aspects of meaning) and systematicity (statistical regularities in forms predict function). Experimental evidence suggests these form-to-meaning correspondences serve different functions in language processing, development, and communication: systematicity facilitates category learning by means of phonological cues, iconicity facilitates word learning and communication by means of perceptuomotor analogies, and arbitrariness facilitates meaning individuation through distinctive forms. Processes of cultural evolution help to explain how these competing motivations shape vocabulary structure.

How arbitrary is language

It is a long established convention that the relationship between sounds and meanings of words is essentially arbitrary—typically the sound of a word gives no hint of its meaning. However, there are numerous reported instances of systematic sound–meaning mappings in language, and this systematicity has been claimed to be important for early language development. In a large-scale corpus analysis of English, we show that sound–meaning mappings are more systematic than would be expected by chance. Furthermore, this systematicity is more pronounced for words involved in the early stages of language acquisition and reduces in later vocabulary development. We propose that the vocabulary is structured to enable systematicity in early language learning to promote language acquisition, while also incorporating arbitrariness for later language in order to facilitate communicative expressivity and efficiency.

The arbitrariness of the sign : learning advantages from the structure of the vocabulary

Recent research has demonstrated that systematic mappings between phonological word forms and their meanings can facilitate language learning (e.g., in the form of sound symbolism or cues to grammatical categories). Yet, paradoxically from a learning viewpoint, most words have an arbitrary form-meaning mapping. We hypothesized that this paradox may reflect a division of labor between 2 different language learning functions: arbitrariness facilitates learning specific word meanings and systematicity facilitates learning to group words into categories. In a series of computational investigations and artificial language learning studies, we varied the extent to which the language was arbitrary or systematic. For both the simulations and the behavioral studies, we found that the optimal structure of the vocabulary for learning incorporated this division of labor. Corpus analyses of English and French indicate that these predicted patterns are also found in natural languages.

Stressing what is important: Orthographic cues and lexical stress assignment

Computational models of reading have typically focused on monosyllabic words. However extending those models to polysyllabic word reading can uncover critical points of distinction between competing models. We present a connectionist model of stress assignment that learned to map orthography onto stress position for English disyllabic words. We compared the performance of the connectionist model to Rastle and Colthearts [(2000).] rule-based model of stress assignment for words and nonwords. The connectionist model performed well on predicting human performance in reading nonwords that both contained and did not contain affixes, whereas the Rastle and Coltheart model performed well only on nonwords with affixes. The connectionist model provides an important first step to simulating all aspects of polysyllabic word reading, and indicates that a probabilistic approach to stress assignment can reflect human performance on stress assignment for both words and nonwords.

Relationships Between Language Structure and Language Learning: The Suffixing Preference and Grammatical Categorization

It is a reasonable assumption that universal properties of natural languages are not accidental. They occur either because they are underwritten by genetic code, because they assist in language processing or language learning, or due to some combination of the two. In this paper we investigate one such language universal: the suffixing preference across the worlds languages, whereby inflections tend to be added to the end of words. A corpus analysis of child-directed speech in English found that suffixes were more accurate at cuing the grammatical category of the root word than were prefixes. An artificial language experiment found that there was a learning advantage for suffixes over prefixes in terms of grammatical categorization within an artificial language. The results are consistent with an account of language universals that originate in general purpose learning mechanisms.

Sleep on it, but only if it is difficult: Effects of sleep on problem solving

Previous research has shown that performance on problem solving improves over a period of sleep, as compared with wakefulness. However, these studies have not determined whether sleep is beneficial for problem solving or whether sleep merely mitigates against interference due to an interruption to solution attempts. Sleep-dependent improvements have been described in terms of spreading activation, which raises the prediction that an effect of sleep should be greater for problems requiring a broader solution search. We presented participants with a set of remote-associate tasks that varied in difficulty as a function of the strength of the stimuli–answer associations. After a period of sleep, wake, or no delay, participants reattempted previously unsolved problems. The sleep group solved a greater number of difficult problems than did the other groups, but no difference was found for easy problems. We conclude that sleep facilitates problem solving, most likely via spreading activation, but this has its primary effect for harder problems.

Learning grammatical categories from distributional cues:Flexible frames for language acquisition

Numerous distributional cues in the childs environment may potentially assist in language learning, but what cues are useful to the child and when are these cues utilised? We propose that the most useful source of distributional cue is a flexible frame surrounding the word, where the language learner integrates information from the preceding and the succeeding word for grammatical categorisation. In corpus analyses of child-directed speech together with computational models of category acquisition, we show that these flexible frames are computationally advantageous for language learning, as they benefit from the coverage of bigram information across a large proportion of the language environment as well as exploiting the enhanced accuracy of trigram information. Flexible frames are also consistent with the developmental trajectory of childrens sensitivity to different sources of distributional information, and they are therefore a useful and usable information source for supporting the acquisition of grammatical categories.