The 41st Language Lunch
Date: 2014-02-07
Location: G.07 Informatics Forum
Against gradual phonologization
Josef,Fruehwald; PPLS; None
The conventional wisdom regarding phonologization is that it progresses as a sequence of gradual reanalyses: natural acoustic, physiological and perceptual phenomena are reanalyzed as gradient coarticulatory processes, which are then reanalyzed as categorical phonological processes (Ohala, 1981; Bermudez-Otero, 2007). I argue that this model of gradual and gradient reanalyses is not well supported by available data on sound change in progress. In fact, based on analyses of the rate of change of multiple vowel variants, and in investigations of mismatches between the predictions based on phonetic versus phonologi- cal grounds, it appears that new phonological processes enter the grammar at the onset of phonetic changes, rather than as later stage reanalyses of phonetic changes in progress.rn
Molecularism about concepts
Richard,Stöckle-Schobel; PPLS; None
One part of the long debate about the nature of concepts has been dominated by the disputes between Conceptual Atomists and Conceptual Holists. A third, middle-ground position, Molecularism, has neither been debated as much nor has it been thoroughly defined yet. I will present two possible ways of construing Molecularism about concepts and I will argue that both are variations of the more commonly held views. To support this view, I will offer to metaphor-based reconstructions of Molecularism – Chemical Molecularism (CheM) and Cluster Molecularism (CluM). CheM is the view that some concepts are constructed from more primitive concepts, which, by virtue of their individual meanings and their combination, provide the meaning of the ‘molecular’ concept.rnrnThis view relies on Atomist premises and faces some of the same problems as Conceptual Atomism. CluM, on the other hand, is a weak kind of Holism that is based on the idea that there are clusters of concepts that have strong relations (e.g. inferential relations, thematic groupings, or family resemblances), which are connected by more general concepts or by weaker links between clusters. CluM still has to answer to some worries Holism faces, such as the problem of Communication. I will end by proposing that CluM is preferable, based on a speculative idea about the relation between concepts and webs of belief.rn
The importance of the source for irony detection
Lorenzo,Bernardini; ILCC; None
Verbal irony is a very complex figure of speech that belongs to the pragmatic level of the language. rnUntil now, however, computational approaches to the detection of irony have only tried to find linguistic clues that could indicate its presence without considering pragmatic factors.rnIn this work, I suggest that an important feature to detect irony in online texts, such as comments of newspaper articles or reviews, is the attribution of the comment to a specific source.rnI present the design of an experiment aimed at evaluating whether the interpretation of an utterance as ironic or not relies on the expectations that the hearer has about the ironic attitude of the source.rnIn order to do so, I’m going to recreate the context of an online newspaper, with news and comments by different users.rnThe hypothesis at test is whether the same sentence is perceived as more or less ironic depending on whether it is attributed to a commentator who is often ironic vs. a commentator who uses irony more rarely.rn
Attribution Relation cues across genres
Alice,Bracchi; ILCC; None
Previous work addressing the automatic detection of opinion and quotation Attribution Relations (ARs) has looked at the cue, the lexical anchor connecting the attributed text to its source, as the central element to the task. Most Attribution Extraction approaches are built upon lists of verb cues that are thought to be sufficiently exhaustive and reliable in signalling ARs in a text.rnThe purpose of this project is to test how reliable such lists are once we move away from the news genre they have mostly been applied to. In order to investigate this, I have compared data from a news corpus annotating attribution cues to a small corpus of thread summaries I have compiled for the purpose. The comparison shows not only that cues are highly genre, register and domain specific, but also that attribution cue analysis should not be restricted to verbs.rnThus, basing an analysis on pre-established lists of generally valid cues, or even attempting to compile new lists from annotated cues, proves to be a highly impracticable solution. rn
Detecting quotations in spoken language
Alessandra,Cervone; ILCC; None
The challenge set by the new field of Attribution Relation Extraction is being able to connect quotations, opinions and other third party information to its rightful source. The work done so far for detecting Attribution Relations (ARs) has dealt only with written text (news and literary genres). Detecting Attribution in speech would also be crucially important, as ARs can represent a source of confusion for speaker identification. However, the crucial role played by punctuation in written texts is replaced in speech by prosody. In order to be able to automatically detect ARs in speech, we should thus consider both the linguistic and the acoustic levels. By analyzing a corpus of informal telephone conversations, the questions that this study is trying to answer are: rnOn the acoustic level: Are there identifiable prosodic clues of attribution in speech? If yes, which are they and what is their role in marking the presence of reported speech? On the linguistic level: Are there any differences between ARs in written and oral texts? And how do ARs change if we switch to an informal register and the dialogue genre?
