Asian and Low-resource Language Information - Impact Factor

Acm Transactions on Asian and Low-resource Language Information Processing | 2023 Impact Factor:2.0 | Cite Score:5.1 | Q2

Impact Factor and Journal Rank of Acm Transactions on Asian and Low-resource Language Information Processing

About: ACM Transactions on Asian and Low-Resource Language Information Processing (TALLIP) is a peer-reviewed journal dedicated to the dissemination of research and development in the field of language information processing for Asian and other low-resource languages. The journal provides a platform for researchers, engineers, and practitioners to share their latest findings and innovations in the domain.
Impact and Significance
ACM Transactions on Asian and Low-Resource Language Information Processing is significant for several reasons:
Focus on Underrepresented Languages: The journal addresses the unique challenges and opportunities associated with Asian and low-resource languages, which are often underrepresented in mainstream NLP research.
Interdisciplinary Research: It promotes interdisciplinary research by bringing together experts from various fields such as linguistics, computer science, and artificial intelligence.
Technological Advancement: The journal highlights advancements in language processing technologies that can have a significant impact on communication, education, and information access.
Global Reach: As part of the ACM digital library, the journal enjoys wide visibility and accessibility among researchers and professionals worldwide.
Rigorous Peer Review: The journal maintains a rigorous peer-review process, ensuring the quality and relevance of published articles.
Types of Articles Accepted
ACM Transactions on Asian and Low-Resource Language Information Processing accepts a variety of submission types, including:
Research Articles: Original research papers presenting new findings and advancements in language information processing.
Review Articles: Comprehensive reviews of the current state of research on specific topics within the journals scope.
Short Communications: Brief reports on novel findings or preliminary research in the field.
Technical Notes: Articles focusing on the development and validation of new techniques and tools for language processing.
Case Studies: Studies demonstrating the application of language processing techniques to solve real-world problems.
Special Issues: Collections of articles focused on specific themes or emerging areas within the scope of the journal.

Journal Home: Journal Homepage

Editor-in-Chief: Imed Zitouni

Scope: ACM Transactions on Asian and Low-Resource Language Information Processing (TALLIP) is a peer-reviewed journal that publishes high-quality research articles, reviews, and surveys on the computational processing of Asian and low-resource languages. The journal aims to address the unique challenges and opportunities presented by these languages in the context of information processing. The journal covers a broad range of topics within language information processing, including but not limited to:
Natural Language Processing (NLP): Research on NLP techniques for Asian and low-resource languages, including syntax, semantics, and pragmatics.
Machine Translation: Studies on translating text between Asian or low-resource languages and other languages, including statistical, neural, and rule-based approaches.
Speech Processing: Research on speech recognition, synthesis, and understanding for Asian and low-resource languages.
Text Mining and Information Retrieval: Studies on extracting information and retrieving relevant data from texts in Asian and low-resource languages.
Corpus Linguistics: Research on the creation, annotation, and utilization of linguistic corpora for Asian and low-resource languages.
Computational Linguistics: Studies on the computational modeling of linguistic phenomena in Asian and low-resource languages.
Language Resources and Evaluation: Research on the development and evaluation of resources such as lexicons, ontologies, and annotated corpora for Asian and low-resource languages.
Language Learning and Education: Studies on the use of computational tools to facilitate language learning and education for Asian and low-resource languages.
Sentiment Analysis and Opinion Mining: Research on analyzing sentiments and opinions expressed in texts in Asian and low-resource languages.
Multilingual and Cross-lingual Processing: Studies on processing and understanding multiple languages, including cross-lingual transfer learning and multilingual models.