33.982, Calls: Computational Linguistics/Israel

[The LINGUIST List]

LINGUIST List: Vol-33-982. Mon Mar 14 2022. ISSN: 1069 - 4875.

Subject: 33.982, Calls: Computational Linguistics/Israel

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Date: Mon, 14 Mar 2022 21:43:18
From: Purificação Silvano [organizers at dislidas.mozajka.co]
Subject: Workshop Discourse Studies and Linguistic Data Science: Addressing challenges in interoperability, multilinguality and linguistic data processing

 
Full Title: Workshop Discourse Studies and Linguistic Data Science: Addressing challenges in interoperability, multilinguality and linguistic data processing 
Short Title: DiSLiDaS 2022 

Date: 24-May-2022 - 24-May-2022
Location: Jerusalem College of Technology, Israel 
Contact Person: Purificação Silvano
Meeting Email: organizers at dislidas.mozajka.co
Web Site: http://dislidas.mozajka.co 

Linguistic Field(s): Computational Linguistics 

Call Deadline: 28-Mar-2022 

Meeting Description:

The purpose of the workshop is to gather current research advances in
discourse analysis and representation, in the context of multilinguality, from
a linguistic and computational perspective. We invite submissions addressing
challenges such as interoperability, linguistic linked open data (LLOD), and
language processing and analysis.


Call for Papers:

The workshop topics are the following (but not limited to):    

Topics:
- Discourse and dialog annotation: Parsing and representation across languages
and frameworks
- Discourse markers and discourse relations (RST, PDTB, SDRT): Identification,
prediction and extraction
- Attitudes discovery and interpretation in Discourse: Appraisal and sentiment
- Effects of multimodality on discourse interpretation: Intonation, gesture
and text
- Interoperability for Multilingual language data: Challenges of rich and
distributed data
- Discourse data and machine learning: Methods and tools

Discourse comprises a wide variety of linguistic phenomena, such as discourse
markers, discourse relations, speaker attitude, that have been largely studied
by different communities of practice from Linguistics and Computation,
rendering several theoretical frameworks (for instance, RST, SDRT, PDTB, for
discourse relations; appraisal theory for sentiment analysis,...), and
technological approaches, such as transformer models, embeddings and alike.
Nonetheless, there are open issues with regards to interoperability,
multilinguality, and language processing, in particular, the existence of
different annotation schemas, disambiguation, lack of training data for
machine learning, scarcity of effective language phenomena detection and
interpretation methods, diverse vocabularies, insufficient multilingual
parallel corpora of non-dialog and dialog, initial stages of exploration of
multimodality. 

Discourse research is one of  the central research areas of natural language
processing (NLP) too. NLP research focuses on formalization, identification
and discovery of semantic phenomena, dialogue exchange structure, and
coherence of text. Some of the technological approaches of NLP include the use
of transformer models, word embeddings, linguistic linked open data,
constitution of aligned multilingual corpora, vocabularies of language
phenomena and alike. Computational discourse explores the evidence that
language consists not only in placing words in the right order but also in
detection and interpretation of the meaning and deeper textual relations as
well as organizing ideas into a logical textual flow. The linguistic
approaches study language phenomena referring to coherence and cohesiveness of
discourse, lexical, phrasal, syntactic, semantic and pragmatic means to
express discourse relations, represent their roles and build language
resources for them.

Despite all the advances, there are still plenty of unresolved problems
related to interoperability, multilinguality, and language processing. With
the growth of the Semantic Web and Linguistic Linked Data, interoperability is
key to read, to interpret and to adopt language resources. The existence of
different annotation schemas to encode discourse relations constitutes a
problem to allow data exchange and re-use on the one hand and to provide
theoretical consistency when producing annotated corpora. Ideally, the model
is custom designed to deal with all the specificities of a particular dataset,
but also broad enough so that it can be applied to other datasets. Many
proposals try to achieve this balance, one of them being ISO 24617. The
treatment of multilinguality is also complicated because of the insufficiency
of multilingual parallel corpora of collections of non-dialog and dialog
texts, that would allow systematic contrastive studies. As to language
processing, the lack of training data for machine learning, coupled with the
scarcity of effective language phenomena detection and interpretation methods,
the coexistence of diverse vocabularies, and the minimal attention to the
contribution of the tone of voice, intonation, gestures to the meaning and the
informative value of discourse elements makes the task of discourse processing
still very challenging.

For submission information, visit:
https://dislidas.mozajka.co/?page_id=43




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LINGUIST List: Vol-33-982	
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