About the Journal

Name of Journal: Computational Linguistics Research Review

About the Journal
Computational Linguistics Research (CLR) is a double-blind peer-reviewed and open access scholarly journal dedicated to advancing the theory, methods, and applications of computational linguistics, natural language processing (NLP), and human–computer language interaction. The journal maintains a rigorous peer review process in which both author and reviewer identities remain concealed, ensuring impartiality and academic integrity. As an open access publication, CLR makes all content freely available without subscription barriers, promoting the global dissemination of high-quality research. The journal adheres to the highest ethical publishing practices, following the COPE (Committee on Publication Ethics) guidelines to uphold transparency, originality, and research integrity. CLR publishes original research articles, technical reports, methodological papers, reviews, and case studies that contribute to the development of computational models, tools, and resources for linguistic analysis and language-enabled technologies.

Aim and Scope

The journal aims to:

  • Advance cutting-edge research in computational linguistics and related disciplines.
  • Provide an inclusive platform for interdisciplinary collaboration between linguistics, computer science, artificial intelligence, and cognitive sciences.
  • Bridge the gap between theoretical linguistic studies and applied computational solutions.
  • Support innovation in language technologies, tools, and resources for academia, industry, and society.
  • Promote global scholarly communication by offering free and open access to all published content.

The scope of CLR includes, but is not limited to:

  • Natural Language Processing (NLP): Syntax, semantics, morphology, and discourse analysis.
  • Machine Learning for Language: Deep learning, transformer models, large language models (LLMs), and statistical NLP.
  • Speech and Multimodal Processing: Speech recognition, synthesis, and integration with visual and gesture-based communication.
  • Machine Translation & Cross-Lingual Technologies: Neural and hybrid translation systems, multilingual NLP, and low-resource language processing.
  • Information Retrieval & Text Mining: Information extraction, sentiment analysis, summarization, and opinion mining.
  • Computational Semantics & Pragmatics: Formal and distributional approaches to meaning.
  • Language Resources & Corpora: Creation, annotation, and evaluation of linguistic datasets and benchmarks.
  • Dialogue Systems & Conversational AI: Chatbots, virtual assistants, and human–machine dialogue modeling.
  • Ethics, Bias, and Fairness in Language Technologies: Responsible AI, data governance, and inclusive language processing.
  • Applications of Computational Linguistics: In education, healthcare, law, social sciences, and business intelligence.