This conference aims at bringing together researchers from across the world working on low-resourced and minority languages to create more speech and language technology for languages of the world.
We invite submissions on topics that include, but are not limited to, the following:
The SPELLL 2025 conference has embraced the Springer Nature Policy regarding AI writing tools, which mandates authors to disclose AI assistance in their research. Springer Nature is monitoring ongoing developments in this area closely and will review (and update) these policies as appropriate.
For more details please visit: https://www.springer.com/gp/editorial-policies/artificial-intelligence--ai-/25428500?srsltid=AfmBOoreWb8ZbuJy6R4k3sh4EFD5mXZ1-g5W7mJn3Siq_4qVKxBC-bZH
In all cases, authors are responsible for the correctness of their methods, results, and writing. Authors should check for potential plagiarism, both of text and code.
Regular submissions must describe substantial, original, completed and unpublished work. Wherever appropriate, concrete evaluation and analysis should be included.
Regular papers may consist of 12 - 16 pages of content including references.
SPELLL 2025 also solicits short papers. Short paper submissions must describe original and unpublished work. Short papers should have a point that can be made in a few pages. Some kinds of short papers are:
Short papers may consist of 6 - 8 pages including references. Short papers will be presented in one or more oral or poster sessions. While short papers will be distinguished from regular papers in the proceedings, there will be no distinction in the proceedings between short papers presented orally and as posters.
For SPELLL 2025, the evaluation of submissions will employ a double-blind review process, ensuring impartiality and confidentiality in the assessment of papers. Under this system, the identities of both the reviewers and the authors are kept anonymous. This means that authors do not know who reviews their papers, and reviewers are unaware of the authors' identities. This approach is designed to minimize biases related to the authors' background, affiliation, or previous work, promoting an objective evaluation based on the submission's originality, relevance, importance, and clarity. Furthermore, authors are required to maintain anonymity in their citations as well. When referring to their previous work, authors should use the third person to avoid revealing their identity. For example, instead of saying "In our earlier work..." or "We previously showed that...", authors should frame these citations as if referencing another researcher's work, such as "Smith et al. (2020) demonstrated that...". This guideline helps preserve the integrity of the double-blind review process, ensuring that papers are evaluated solely on their merits.
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Word Template: https://resource-cms.springernature.com/springer-cms/rest/v1/content/19238706/data/v5Overleaf link: https://www.overleaf.com/
Accepted papers that are presented at the conference will be published in the Springer series: Communications in Computer and Information Science (CCIS).
Volumes published will be indexed in DBLP, Google Scholar, EI-Compendex, Mathematical Reviews, SCImago, Scopus. CCIS volumes are also submitted for the inclusion in ISI Proceedings.