Language technologies and their applications are an integral and critical part of our daily lives. Many of these technologies have their roots in academic and industrial laboratories where researchers invented a plethora of algorithms, benchmarked them against shared datasets and perfected their performance to provide plausible solutions to real-world applications. While a controlled laboratory setting is vital for a deeper scientific understanding of the problems underlying language technologies and the impact of algorithmic design choices on their performance, transitioning the technology to real-world industrial strength applications raises a different, yet challenging, set of technical issues.
The EACL 2027 Industry Track aims to highlight this mutual influence of language technology in academia and industry, which has significantly contributed to the proliferation of industry applications. The track - following the tradition of related industry track series at EACL, NAACL, ACL and EMNLP - provides the opportunity for researchers, engineers, practitioners and users to meet and discuss the latest language technologies methods as deployed in a real-world setting and aims to be the premier forum for knowledge sharing across the boundary between academia and industry.
We invite submissions describing innovations and implementations in all areas of speech and natural language processing technologies and systems that are relevant to real-word applications. The primary focus of this track is on papers that advance the understanding of, and demonstrate the effective handling of, practical issues related to the deployment of language processing technologies in real-world use application. We encourage submissions from industry, non-profit, government, and public-sector organisations, with the understanding that the end-users of these systems extend beyond the NLP community. Please note that if submissions involve proprietary data, there is no requirement to make this data available.