The recruitment of knowledge regarding plurality and compound formation during language comprehension

Compound formation has been a major focus of research and debate in mental lexicon research. In particular, it has been widely observed that compounds with a regular plural non-head are dispreferred, and a long line of research has examined the nature of this constraint, including which morphological, semantic or phonological properties of the non-head underlie this dispreference. While it is typically assumed that this constraint in fact leads to the barring of a compound analysis to a noun-noun string which would otherwise violate the constraint, its implementation during sentence comprehension has not been thoroughly examined. Using self-paced reading, we demonstrate that knowledge of pluralization and compound formation is immediately utilized in the assignment of structure to noun-noun strings, and that the dispreference for regular plural non-heads in fact leads the parser away from the compound analysis in favor of a more complex grammatical alternative. These results provide new evidence for the online deployment of knowledge regarding pluralization and its interaction with compound formation, and inform our understanding of how morphological information is deployed during, and impacts real-time sentence comprehension

Features and Functions: Decomposing the Neural and Cognitive Bases of Semantic Composition

In this dissertation, I present a suite of studies investigating the neural and cognitive bases of semantic composition. First, I motivate why a theory of semantic combinatorics is a fundamental desideratum of the cognitive neuroscience of language. I then introduce a possible typology of semantic composition: one which involves contrasting feature-based composition with function-based composition. Having outlined several different ways we might operationalize such a distinction, I proceed to detail two studies using univariate and multivariate fMRI measures, each examining different dichotomies along which the feature-vs.-function distinction might cleave. I demonstrate evidence that activity in the angular gyrus indexes certain kinds of function-/relation-based semantic operations and may be involved in processing event semantics. These results provide the first targeted comparison of feature- and function-based semantic composition, particularly in the brain, and delineate what proves to be a productive typology of semantic combinatorial operations. The final study investigates a different question regarding semantic composition: namely, how automatic is the interpretation of plural events, and what information does the processor use when committing to either a distributive plural event (comprising separate events) or a collective plural event (consisting of a single joint event)

An infrastructure for Turkish prosody generation in text-to-speech synthesis

Text-to-speech engines benefit from natural language processing while generating the appropriate prosody. In this study, we investigate the natural language processing infrastructure for Turkish prosody generation in three steps as pronunciation disambiguation, phonological phrase detection and intonation level assignment. We focus on phrase boundary detection and intonation assignment. We propose a phonological phrase detection scheme based on syntactic analysis for Turkish and assign one of three intonation levels to words in detected phrases. Empirical observations on 100 sentences show that the proposed scheme works with approximately 85% accuracy

Statistical model of human lexical category disambiguation

Research in Sentence Processing is concerned with discovering the mechanism by which linguistic utterances are mapped onto meaningful representations within the human mind. Models of the Human Sentence Processing Mechanism (HSPM) can be divided into those in which such mapping is performed by a number of limited modular processes and those in which there is a single interactive process. A further, and increasingly important, distinction is between models which rely on innate preferences to guide decision processes and those which make use of experiencebased statistics. In this context, the aims of the current thesis are two-fold: • To argue that the correct architecture of the HSPM is both modular and statistical - the Modular Statistical Hypothesis (MSH). • To propose and provide empirical support for a position in which human lexical category disambiguation occurs within a modular process, distinct from syntactic parsing and guided by a statistical decision process. Arguments are given for why a modular statistical architecture should be preferred on both methodological and rational grounds. We then turn to the (often ignored) problem of lexical category disambiguation and propose the existence of a presyntactic Statistical Lexical Category Module (SLCM). A number of variants of the SLCM are introduced. By empirically investigating this particular architecture we also hope to provide support for the more general hypothesis - the MSH. The SLCM has some interesting behavioural properties; the remainder of the thesis empirically investigates whether these behaviours are observable in human sentence processing. We first consider whether the results of existing studies might be attributable to SLCM behaviour. Such evaluation provides support for an HSPM architecture that includes this SLCM and allows us to determine which SLCM variant is empirically most plausible. Predictions are made, using this variant, to determine SLCM behaviour in the face of novel utterances; these predictions are then tested using a self-paced reading paradigm. The results of this experimentation fully support the inclusion of the SLCM in a model of the HSPM and are not compatible with other existing models. As the SLCM is a modular and statistical process, empirical evidence for the SLCM also directly supports an HSPM architecture which is modular and statistical. We therefore conclude that our results strongly support both the SLCM and the MSH. However, more work is needed, both to produce further evidence and to define the model further

Age-Related Changes to the Production of Linguistic Prosody

The production of speech prosody (the rhythm, pausing, and intonation associated with natural speech) is critical to effective communication. The current study investigated the impact of age-related changes to physiology and cognition in relation to the production of two types of linguistic prosody: lexical stress and the disambiguation of syntactically ambiguous utterances. Analyses of the acoustic correlates of stress: speech intensity (or sound-pressure level; SPL), fundamental frequency (F0), key word/phrase duration, and pause duration revealed that both young and older adults effectively use these acoustic features to signal linguistic prosody, although the relative weighting of cues differed by group. Differences in F0 were attributed to age-related physiological changes in the laryngeal subsystem, while group differences in duration measures were attributed to relative task complexity and the cognitive-linguistic load of these respective tasks. The current study provides normative acoustic data for older adults which informs interpretation of clinical findings as well as research pertaining to dysprosody as the result of disease processes