35.663, Calls: ATTENDĔRE: Tra Attesa e Attenzione

[The LINGUIST List]

LINGUIST List: Vol-35-663. Mon Feb 26 2024. ISSN: 1069 - 4875.

Subject: 35.663, Calls: ATTENDĔRE:  Tra Attesa e Attenzione

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Date: 26-Feb-2024
From: Lorenzo Cambi [lorenzo.cambi at unifi.it]
Subject: ATTENDĔRE:  Tra Attesa e Attenzione


Full Title: ATTENDĔRE:  Tra attesa e attenzione
Short Title: FLUI

Date: 19-Jun-2024 - 21-Jun-2024
Location: Florence, Italy
Contact Person: Lorenzo Cambi
Meeting Email: lorenzo.cambi at unifi.it
Web Site: https://sites.google.com/unifi.it/flui

Linguistic Field(s): Applied Linguistics; Computational Linguistics;
General Linguistics; Sociolinguistics; Syntax
Subject Language(s): English (eng)
                     Italian (ita)

Call Deadline: 05-Apr-2024

Meeting Description:

The conference will focus on attention and waiting from linguistic,
literary and philological perspectives.
We suggest some possible submission topics: in the sociolinguistics
field the attention is crucial in assessing stylistic variation;
studies on prosody and syntax focus on topicalization mechanisms; the
role of attention in learning processes explored by applied
linguistics; moreover, the new role of attention highlighted by
artificial intelligences.
These are just a few suggested lines of research, for more information
please see the call for papers:
https://sites.google.com/unifi.it/flui/call-for-papers-ita (ITALIAN)
https://sites.google.com/unifi.it/flui/call-for-papers-eng (ENGLISH)

Call for Papers:

The main topic of the conference focuses on two terms, "waiting" and
"attention", that are derived, both semantically and etymologically,
from the Latin verb attendĕre, which indicates the action of directing
mind, thoughts, and hopes towards a specific object, encompassing both
the meanings of 'to apply' and 'to wait'. [...]. This topic can be
analyzed from the point of view of philology,literature and
linguistics, even  through the innovative tools of the so-called
digital humanities. Some possible submission topics are listed below.

[...]

In Linguistics, the topics listed above could be analyzed from two
perspectives: on one hand, the mechanisms used by speakers to
emphasize or pay attention on the most interesting element in the
communication; on the other hand, the selection and control processes
made on language in the act of communication, focusing on the
connection between reality and the speaker.
- Concerning the first meaning, numerous studies have highlighted how
voice modulates intensity, fundamental frequency, or duration to give
prominence to specific segments of a communicative act. From a
syntactic point of view, there are numerous strategies to mark certain
elements rather than others, including topicalization. In pragmatics,
the study of attention getters signals, for example in perception
verbs, allows for a broader view not only towards a
comparative-contrastive study but also towards research in a
diachronic perspective. Attention-getting strategies can also help to
discern between pathological and non-pathological speech, as shown by
recent works on schizophrenia.
- As for the second meaning, a paradigmatic example is found in
sociolinguistics, where attention is a fundamental aspect for
evaluating stylistic variation. Two models are mainly used for this
task:  the attention-to-speech one, according to which a more
prestigious variety is used in a controlled situation, and the
attention-to-self model, whereby a speaker, in a situation of high
communicative attention, may choose to use a minority language variety
to emphasize their cultural identity. Furthermore, hypercorrections
originated from the influence exerted by a prestigious variety,
constitute valuable synchronous and diachronic evidence to understand
linguistic selection processes.

In the field of Digital Humanities, the theme of attention inevitably
intersects with the possibility, given by automation processes, to
handle and analyze large amounts of data in a short amount of time.
Depending on the research focus, digitization allows for the easy
identification and quantification of elements,  their occurrences and
their mutual relationships,  possibly highlighting relevant features
for the task:
- In Machine Learning (ML), Attention is the mechanism Artificial
Intelligences (AI) use to assign a relevance value to a word within
its context. The advent of Transformers, the neural network
architecture based on the Attention mechanism underlying Large
Language Models such as ChatGPT, LLAMA, and Mistral, has profoundly
revolutionized computational linguistics (CL): these architectures
set a new turning point in many CL tasks, from machine translation to
parsing, from generative AI tasks such as Q&A (question answering) and
Text Generation to Summarization.
- Data annotation at multiple levels finds full application in the
field of linguistics, for example in collecting corpora of spontaneous
or semi-spontaneous speech, leading to the need to diversify among
multiple communicative contexts, in which speakers’ attention and
pragmatic-linguistic strategies vary.

[...]

The application is open to PhD students, post-docs, and young
researchers. [...] . Talks of max. 20 minutes are expected, and
proposals in Italian and English will be accepted. Please submit your
anonymous proposal paper (300 words max., excluding title, tables,
graphs, and bibliography) as one PDF file via the Google form
(https://forms.gle/CgMttGAiABgf69ZY9).



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