Salient Language in Context (SLIC): a web app for collecting real-time attention data in response to audio samples

Abstract This article introduces Salient Language in Context (SLIC), a web application designed for collecting real-time attention data from listeners in response to audio samples. SLIC enables researchers to capture timestamped attention points as listeners engage with spoken language, allowing for an innovative approach to studying real-time perception of speech. The application facilitates the collection of both quantitative and qualitative data, providing researchers with not only precise reaction timing but also listener justifications for their responses. SLIC addresses long-standing challenges in sociolinguistics and perceptual dialectology by enabling researchers to examine which linguistic features capture attention, when they do so, and how listeners interpret them in context. The technical aspects of SLIC are discussed in the article and include its secure online infrastructure and integration with scripts written for Praat, which allow for efficient data visualization and interpretation. A case study using SLIC demonstrates its effectiveness in examining listener perceptions of segmental features in Liverpool English, revealing distinct patterns of attention and commentary strategies. By providing a robust method for investigating real-time language perception, SLIC has a broad range of potential applications.