User-Centered Design of Digital Tools for Sociolinguistic Studies in Under-Resourced Languages (2024)

Abstract: Investigating language variation is a core aspect of sociolinguistics, especially through the use of linguistic corpora. Collecting and analyzing spoken language in text-based corpora can be time-consuming and error-prone, especially for under-resourced languages with limited software assistance. This paper explores the language variation research process using a User-Centered Design (UCD) approach from the field of Human-Computer Interaction (HCI), offering guidelines for the development of digital tools for sociolinguists. We interviewed four researchers, observed their workflows and software usage, and analyzed the data using Grounded Theory. This revealed key challenges in manual tasks, software assistance, and data management. Based on these insights, we identified a set of requirements that future tools should meet to be valuable for researchers in this domain. The paper concludes by proposing design concepts with sketches and prototypes based on the identified requirements. These concepts aim to guide the implementation of a fully functional, open-source tool. This work presents an interdisciplinary approach between sociolinguistics and HCI by emphasizing the practical aspects of research that are often overlooked.

## introduction researchers in sociolinguistics often use corpora for investigations of language structure and usage, identifying linguistic characteristics and patterns in different contexts. researchers gain insights into these patterns by analyzing a collection of authentic texts (corpora) quantitatively and/or qualitatively @xcite . the importance of this field has particularly increased due to factors such as global interconnection and continuous increase in migration. notably, the growing contact of speakers of * these authors contributed equally to this work. different languages and varieties adds relevance to investigating and analyzing language variation and change. this research often involves collecting and transcribing natural spoken language to identify distinct linguistic features and discover patterns during analysis, though other methods, such as sociolinguistic experiments, are also employed. yet, the potential of this research area is frequently accompanied by many challenges that influence how research is conducted. for instance, the exponential increase of available data enhances the possibilities for research, but dealing with these large quantities of data poses new challenges for researchers and requires them to incorporate computer-assisted tools @xcite . however, transitioning to digital solutions can be difficult when faced with unfamiliar tools and a lack of knowledge about research strategies. in underresourced languages, these issues are often compounded by the absence of assistance tools, like automatic language recognition software, leading to a time-consuming manual transcription process @xcite . this transcription bottleneck @xcite is particularly problematic for under-resourced languages due to transcription difficulties. this raises the question of whether current research techniques can keep up with advancing technology and changing language dynamics. in this paper, we aim to create a bridge between human-computer interaction (hci) and linguistics, fostering an interdisciplinary collaboration that leverages the strengths of both fields. by focusing on a user-centered design (ucd) approach, we investigate the practical workflows currently carried out by variationist sociolinguists working with lesser-resourced languages, using research on arabic dialects as a case study. we aim to identify critical areas, such as data management, digital annotation, and automatic analysis, that limit the efficiency and quality of their studies. the outcomes intended to be applicable to a broader range 1 12 ## theoretical background and related work this section reviews the theoretical background and relevant literature. central to this discussion is an exploration of user-centered design principles and their various extensions (section 2.1), which are crucial to our approach. additionally, we present an overview of current software solutions in this domain (section 2.5). while our work touches on language variation research, we primarily focus on ucd aspects in this section. for more detailed information on language variation research methods, please refer to tagliamonte (2006). ## methodology this section details the strategies for data collection (section 3.1) and analysis (section 3.2). it also describes how these results inform user requirements (section 3.3), which are the core findings of this paper. ## results this section presents the findings from our grounded theory analysis, using open and axial coding to uncover key themes in language variation research (section 4.1). we highlight the heavy reliance on manual processes and sparse use of software tools. a comprehensive summary is provided in figure 2 . the analysis identified central themes that guided us in understanding user requirements (see section 4.2). ## future directions: engaging users in design and development even after gathering user requirements, continuing to incorporate user feedback is crucial throughout the design and implementation phases of software development. the initial concept stage focuses on developing design solutions based on previously identified user needs, as well as employing prototypes to test and refine created design solutions. this approach ensures that the design effectively meets user expectations and informs the implementation process in later stages of development. ## conclusion sociolinguists studying language variation in under-resourced languages often lack supporting software tools. addressing this requires an interdisciplinary perspective across sociolinguistics and human-computer interaction. this paper provides such a perspective and actualizes it with a ucd approach. our empirical work is motivated to understand, respect, and support the unique requirements of sociolinguists in their workflows. to this end, we collected rich qualitative data through interviews and observations with various academics researching language variation. our participants were recruited from different academic institutions in europe, and all focus on studying arabic dialects. this data revealed key challenges that sociolinguists encounter during their work, arising from the practice of error-prone manual text analysis and inconsistent data management approaches. the underlying root cause is a lack of software tools tailored to meet sociolinguists' specific requirements in the context of language variation research. this leads to further difficulties and inefficiencies during the research process. it is important to note that sociolinguists studying different languages, particularly those without formal writing systems, or working in different academic contexts, may face unique challenges that require tailored solutions. thus, while our study provides valuable insights, it may not encompass all the needs of sociolinguistic researchers worldwide. based on these insights, we specified a set of concrete user requirements, which serve as a guideline for the design and development of better software tools. by introducing the idea of sketches and prototypes, we have illustrated how these requirements can be leveraged constructively. we plan to 8 implement these ideas in a functional open-source tool. beyond our specific study here, we hope that this paper stimulates interdisciplinary perspectives to facilitate the often overlooked practical side of sociolinguistic research work. 9 20 figure 3 presents a visualization of the twelve code groups extracted from the axial coding stage, as part of grounded theory methodology. this illustration is designed to enhance clarity by focusing on the most critical relationships and code groups from the data. in the provided context, the variables (colored in turquoise) signify specific linguistic features (dependent variables) or speaker attributes (independent variables). 4 as can be seen from the figure, data management is a key challenge in research workflows, directly impacting the creation of variables and the efficiency of annotation. it contrasts manual, error-prone tasks with the potential for increased efficiency and reduced errors through automated processes, underscoring our findings that automation is a desirable, though not yet fully realized, goal in language variation research. the diagram further delineates the ripple effect of data management on research output. effective management is shown to allow for the incorporation of more variables, which can lead to richer, more nuanced research. however, this also introduces a trade-off between the potential benefits of having more variables and the additional effort required to manage them.