An Exploration of Semantic Features in an Unsupervised Thematic Fit Evaluation Framework

Thematic fit is the extent to which an entity fits a thematic role in the semantic frame of an event, e.g., how well humans would rate “knife” as an instrument of an event of cutting. We explore the use of the SENNA semantic role-labeller in defining a distributional space in order to build an unsupervised model of event-entity thematic fit judgements. We test a number of ways of extracting features from SENNA-labelled versions of the ukWaC and BNC corpora and identify tradeoffs. Some of our Distributional Memory models outperform an existing syntax-based model (TypeDM) that uses hand-crafted rules for role inference on a previously tested data set. We combine the results of a selected SENNA-based model with TypeDM’s results and find that there is some amount of complementarity in what a syntactic and a semantic model will cover. In the process, we create a broad-coverage semantically-labelled corpus

Modelling Incremental Self-Repair Processing in Dialogue.

PhDSelf-repairs, where speakers repeat themselves, reformulate or restart what they are saying, are pervasive in human dialogue. These phenomena provide a window into real-time human language processing. For explanatory adequacy, a model of dialogue must include mechanisms that account for them. Artificial dialogue agents also need this capability for more natural interaction with human users. This thesis investigates the structure of self-repair and its function in the incremental construction of meaning in interaction. A corpus study shows how the range of self-repairs seen in dialogue cannot be accounted for by looking at surface form alone. More particularly it analyses a string-alignment approach and shows how it is insufficient, provides requirements for a suitable model of incremental context and an ontology of self-repair function. An information-theoretic model is developed which addresses these issues along with a system that automatically detects self-repairs and edit terms on transcripts incrementally with minimal latency, achieving state-of-the-art results. Additionally it is shown to have practical use in the psychiatric domain. The thesis goes on to present a dialogue model to interpret and generate repaired utterances incrementally. When processing repaired rather than fluent utterances, it achieves the same degree of incremental interpretation and incremental representation. Practical implementation methods are presented for an existing dialogue system. Finally, a more pragmatically oriented approach is presented to model self-repairs in a psycholinguistically plausible way. This is achieved through extending the dialogue model to include a probabilistic semantic framework to perform incremental inference in a reference resolution domain. The thesis concludes that at least as fine-grained a model of context as word-by-word is required for realistic models of self-repair, and context must include linguistic action sequences and information update effects. The way dialogue participants process self-repairs to make inferences in real time, rather than filter out their disfluency effects, has been modelled formally and in practical systems.Engineering and Physical Sciences Research Council (EPSRC) Doctoral Training Account (DTA) scholarship from the School of Electronic Engineering and Computer Science at Queen Mary University of London

Generating referring expressions in a domain of objects and processes

This thesis presents a collection of algorithms and data structures for the generation of pronouns, anaphoric definite noun phrases, and one-anaphoric phrases. After a close analysis of the particular kinds of referring expressions that appear in a particular domain -that of cookery recipes -the thesis presents an appropriate ontology and a corresponding representation language. This ontology is then integrated into a wider framework for language generation as a whole, whereupon we show how the representation language can be successfully used to produce appropriate referring expressions for a range of complex object types.Amongst the more important ideas explored in the thesis are the following:• We introduce the notion of a generalized physical object as a way of representing singular entities, mass entities, and entities which are sets.• We adopt the view that planning operators are essentially underspecified events, and use this, in conjunction with a simple model of the hearer, to allow us to determine the appropriate level of detail at which a given plan should be described.• We make use of a discourse model that distinguishes local and global focus, and is closely tied to a notion of discourse structure; and we introduce a notion of DISCRIMINATORY POWER as a means to choosing the content of a referring expression.• We present a model of the generation of referring expressions that makes use of two levels of intermediate representation, and integrate this model with the use of a linguistically- founded grammar for noun phrases.The thesis ends by making some suggestions for further extensions to the work reported here

Proceedings of the Fifth Italian Conference on Computational Linguistics CLiC-it 2018 : 10-12 December 2018, Torino

On behalf of the Program Committee, a very warm welcome to the Fifth Italian Conference on Computational Linguistics (CLiC-­‐it 2018). This edition of the conference is held in Torino. The conference is locally organised by the University of Torino and hosted into its prestigious main lecture hall “Cavallerizza Reale”. The CLiC-­‐it conference series is an initiative of the Italian Association for Computational Linguistics (AILC) which, after five years of activity, has clearly established itself as the premier national forum for research and development in the fields of Computational Linguistics and Natural Language Processing, where leading researchers and practitioners from academia and industry meet to share their research results, experiences, and challenges

Word Knowledge and Word Usage

Word storage and processing define a multi-factorial domain of scientific inquiry whose thorough investigation goes well beyond the boundaries of traditional disciplinary taxonomies, to require synergic integration of a wide range of methods, techniques and empirical and experimental findings. The present book intends to approach a few central issues concerning the organization, structure and functioning of the Mental Lexicon, by asking domain experts to look at common, central topics from complementary standpoints, and discuss the advantages of developing converging perspectives. The book will explore the connections between computational and algorithmic models of the mental lexicon, word frequency distributions and information theoretical measures of word families, statistical correlations across psycho-linguistic and cognitive evidence, principles of machine learning and integrative brain models of word storage and processing. Main goal of the book will be to map out the landscape of future research in this area, to foster the development of interdisciplinary curricula and help single-domain specialists understand and address issues and questions as they are raised in other disciplines

Proceedings of the Fifth Italian Conference on Computational Linguistics CLiC-it 2018

On behalf of the Program Committee, a very warm welcome to the Fifth Italian Conference on Computational Linguistics (CLiC-­‐it 2018). This edition of the conference is held in Torino. The conference is locally organised by the University of Torino and hosted into its prestigious main lecture hall “Cavallerizza Reale”. The CLiC-­‐it conference series is an initiative of the Italian Association for Computational Linguistics (AILC) which, after five years of activity, has clearly established itself as the premier national forum for research and development in the fields of Computational Linguistics and Natural Language Processing, where leading researchers and practitioners from academia and industry meet to share their research results, experiences, and challenges

The acquisition of phonology in the first year of life

Any phonological theory needs to encompass an account of acquisition and any account of acquisition must take its place within a general theory of phonology. This thesis aims to ascribe phonological significance to speech perception in infancy, a move impossible unless phonology is defined, as it is here, from both a psycholinguistic and a formal viewpoint as a dedicated pattern-recognition system. Extant results from infant studies are reviewed and aligned with current phonological theory. In particular, such theory characterises phonology as bi-modular, so the acquisition of individual melodic and prosodic modules and their subsequent orientation with respect to one another must constitute three different developmental tasks. This delivers a relatively simple account of the mapping between psychoacoustics and phonology. Perception and pre-existing theories of segmental complexity are related using an original experiment into the perception of vowel-height contrast in Catalan. If infant perception has phonological import, then disparate phonetic reflexes which are predicted as phonologically identical should show parallels in acquisition. General theory argues that the same abstract melodic objects underlie both laryngeal contrasts in stops and lexical tonal contrasts. Earlier studies show that language-specific attunement to stop contrasts has taken place by the age of six months. New tests are now reported, using children of the same age, which demonstrate that infants acquiring Yorùbá, a language which has a three-way contrast for tone, attend more closely to pitch changes within the minimal domain word than do English controls. Further, they only attend to those pitch changes that possess phonological import within that domain in the steady-state language. In this their perception exactly parallels that displayed by adult speakers. Apparent anomalies in the results of these tests are shown to be closely parallelled by phonological asymmetries in the tonology of Yorùbá

Human-Computer Interaction

In this book the reader will find a collection of 31 papers presenting different facets of Human Computer Interaction, the result of research projects and experiments as well as new approaches to design user interfaces. The book is organized according to the following main topics in a sequential order: new interaction paradigms, multimodality, usability studies on several interaction mechanisms, human factors, universal design and development methodologies and tools