Introducing the Digital Language Equality Metric: Technological Factors (2022)

Abstract: This paper introduces the concept of Digital Language Equality (DLE) developed by the EU-funded European Language Equality (ELE) project, and describes the associated DLE Metric with a focus on its technological factors (TFs), which are complemented by situational contextual factors. This work aims at objectively describing the level of technological support of all European languages and lays the foundation to implement a large-scale EU-wide programme to ensure that these languages can continue to exist and prosper in the digital age, to serve the present and future needs of their speakers. The paper situates this ongoing work with a strong European focus in the broader context of related efforts, and explains how the DLE Metric can help track the progress towards DLE for all languages of Europe, focusing in particular on the role played by the TFs. These are derived from the European Language Grid (ELG) Catalogue, that provides the empirical basis to measure the level of digital readiness of all European languages. The DLE Metric scores can be consulted through an online interactive dashboard to show the level of technological support of each European language and track the overall progress toward DLE.

## technological factors in order to quantify the level of technological support for a language, we consider a set of tfs. here we briefly describe their main categories, illustrating the breadth and diversity of the lrs and tools that they capture. the first category of tfs includes tools and services that are offered via the web or running in the cloud, but also downloadable tools, source code, etc.; this category encompasses, for example, nlp tools (morphological analysers, part-of-speech taggers, lemmatisers, parsers, etc.); authoring tools (e. g. spelling, grammar and style checkers); services for information retrieval, extraction, and mining, text and speech analytics, machine translation, natural language understanding and generation, speech technologies, conversational systems, etc. the second category of tfs includes datasets, i. e. corpora or collections of text documents, text segments, audio transcripts, audio and video recordings, etc., monolingual or bi-/multilingual, raw or annotated. it also encompasses language models and computational grammars and lexical and conceptual resources, including resources organised on the basis of lexical or conceptual entries (lexical items, terms, concepts, etc.) with their supplementary information (e. g., grammatical, semantic, statistical information, etc.), such as computational lexica, gazetteers, ontologies, term lists, thesauri, etc. the technological component of the dle metric and the resulting technological dle score per language are based on the number of lrs available for a given language. although an essential aspect of a language's digital readiness is the number of available lrs, equally important are the types and features of these lrs, insofar as they indicate how well a language is supported in all different lt areas. to capture such aspects with the dle metric, in addition to raw counts of available lrs, the following features of lrs have also been taken into account: ## conclusions and future work we introduce the notion of dle and describe the dle metric, focusing in particular on the technological dle score, as developed in the ele project. by providing an empirically-grounded and realistic quantification of the level of technological support possessed by the languages of europe, the dle metric, whose tfs are complemented by the cfs, will contribute to the formulation of the sustainable evidence-based sria and roadmap that will drive future efforts in equipping all european languages with the lts needed to achieve full dle in europe by 2030; the dle metric will also provide a transparent means to track and monitor the actual progress in this direction. with regard to the tfs, the close collaboration with the sister project elg has been particularly valuable, in that the tfs rely on the metadata in the elg catalogue as the ground truth and empirical foundation to measure and quantify the level of digital readiness of the languages covered by ele. the overview of the tfs is accompanied by an in-depth discussion of the scoring and weighting mechanism adopted for the computation of the technological dle score, that is illustrated to explain the overall design of the features and values that contribute to the tfs. the weights assigned to the features to compute the technological dle score can be adjusted going forward. this approach would be useful to address developments ensuing from advances made in lt and as new paradigms or technologies become the state of the art, potentially also as new types of resources emerge and are recognised as crucial for lt support. the ele consortium views the dle metric as a flexible tool, with the possibility of updating and revising if and as needed the exact configuration of the tfs and cfs. we are confident that the concept of dle and its associated metric described here represent valuable tools on which to base subsequent efforts to measure and improve the readiness of europe's languages for the digital age, also taking into account the situational contexts in which the languages are used via the cfs. by drawing on the descriptive, diagnostic and predictive value of the dle metric, the community will have a solid and verifiable means of pursuing and evaluating muchneeded developments in the interest of all european citizens. in conclusion, we hope that the dle metric will be recognised as a helpful tool by a range of stakeholders at various local, regional, national and european levels who are committed to preventing the extinction of european languages under threat, and who are interested in promoting their prosperity. such stakeholders include decision-and policy-makers, industry leaders, researchers, developers, and citizens across europe who will drive forward future developments in the fields of lt and language-centric ai.