Chapter 5. Discourse markers and discourse relations

Author(s):  
Adriana Costăchescu
2021 ◽  
Vol 112 (7) ◽  
pp. 39-64
Author(s):  
Katharina König

The paper is concerned with codeswitching in transmodal WhatsApp messenger chats. Based on a corpus of text and audio postings from a group of German-Lebanese cousins that is complemented by ethnographic interviews, the study shows that language alternations can be associated with particular metapragmatic or indexical functions in the different modalities. In audio postings, switching between German and Arabic contextualises varying discourse relations. Also, the cousins use Arabic discourse markers (such as ya'ne, ‘it means’) frequently to structure their talk. In contrast, when they switch to Arabic in their text-postings – using Arabizi, a CMC-register in the Arabic-speaking world – this recurrently establishes a playful or ironic frame for ritual teasings. The final section discusses these transmodal and multilingual practices as multi-layered identity positionings vis-à-vis a monolingual society, their multilingual family and networked communities.


2020 ◽  
Vol 11 (2) ◽  
Author(s):  
Amir Zeldes ◽  
Yang Liu

Previous data-driven work investigating the types and distributions of discourse relation signals, including discourse markers such as 'however' or phrases such as 'as a result' has focused on the relative frequencies of signal words within and outside text from each discourse relation. Such approaches do not allow us to quantify the signaling strength of individual instances of a signal on a scale (e.g. more or less discourse-relevant instances of 'and'), to assess the distribution of ambiguity for signals, or to identify words that hinder discourse relation identification in context ('anti-signals' or 'distractors'). In this paper we present a data-driven approach to signal detection using a distantly supervised neural network and develop a metric, Δs (or 'delta-softmax'), to quantify signaling strength. Ranging between -1 and 1 and relying on recent advances in contextualized words embeddings, the metric represents each word's positive or negative contribution to the identifiability of a relation in specific instances in context. Based on an English corpus annotated for discourse relations using Rhetorical Structure Theory and signal type annotations anchored to specific tokens, our analysis examines the reliability of the metric, the places where it overlaps with and differs from human judgments, and the implications for identifying features that neural models may need in order to perform better on automatic discourse relation classification.


2019 ◽  
Vol 26 (2) ◽  
pp. 114-134
Author(s):  
Сергій Засєкін

Traditionally, translation is viewed as a reliable shield over linguistic diversity, one of the ways to ensure a target language survival. However, translation is also reported to distort a translated language due to introducing ‘the third code’ (Frawley, 1984) features. These “deforming tendencies” (Berman, 1985) destroy the translated language by erasing its natural pattern and by adding there a bundle of alien features that cause its lexical, syntactical, and stylistic deficiencies. The current study is aimed at detecting those destructive features treated in translation studies as “translation universals” (Chesterman, 2004). To this end, a psycholinguistic analysis was held to establish the use of language which is not the result of intentional, controlled processes and of which translators may not be aware. These subliminal translation-inherent processes can be traced in the use of function words that encode procedural meaning. Relevance Theory (Wilson & Sperber, 1993) explains a conceptual-procedural distinction as a major distinction made between two types of linguistically encoded information. Conceptual information expressed by content words is viewed as encoding concepts whereas words with procedural meaning contribute to the derivation of implicatures, certain ways of processing propositions. Discourse connectives, conjunctions, prepositions, particles, pronouns, modal words constitute that group of function words with procedural meaning. To uncover certain variations in the use of these linguistic units, a parallel English-Ukrainian corpus made up of an 8,000-character excerpt from Franny by J.D. Salinger, its professional translation, and forty novice translators’ target versions, was compiled. The corpus data were processed by Textanz and SPSS computerized tools. The results of the psycholinguistic analysis proved that the Ukrainian versions as contrasted to the original text contained the following S-universals: implicitation expressed through the shortage of discourse markers of global coherence, simplification due to the lack of personal pronouns, decreased mean number of words per sentence, and greater number of sentences; normalization embodied in vernacular network impoverishment due to the decreased amount of pragmatic markers and fillers, explicitation due to higher lexical variety and density rates, and rationalization as a result of abundant marking of discourse relations. Conclusions. Taken together, these findings have significant implications for the understanding of how procedural information processing by novice translators is manifested in translation.


2020 ◽  
Vol 29 (2) ◽  
pp. 179-190
Author(s):  
Wha Soo Kim ◽  
Ji Woo Lee ◽  
Mi Ji Kim ◽  
Hu In Lee ◽  
Eun Young Jang

2018 ◽  
Vol 27 ◽  
pp. 45-68
Author(s):  
Miran Kim ◽  
◽  
Minjeong Seo ◽  
Namjoong Kim ◽  
Ok Kyung Koo

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