Second Language Acquisition and the Semiotics of Lyrics: An AI-Mediated Theoretical Approach

Abstract

This article explores the intersection of Second Language Acquisition (SLA) and the semiotic analysis of song lyrics, proposing an innovative framework where Artificial Intelligence (AI) serves as both medium and mediator. Drawing on mediated theoretical approaches, the study investigates how AI-powered tools can decode and interpret the symbolic and cultural meanings embedded in lyrics, offering enhanced insight into language learning processes. Lyrics, as multimodal texts, are rich in metaphors, idioms, and socio-cultural references, making them potent tools for SLA. However, traditional pedagogical models often overlook the interpretive complexity of these texts. By integrating AI-driven semiotic analysis, this paper demonstrates how learners can engage more critically and contextually with lyrical content, thereby deepening linguistic competence and cultural literacy. The article employs a qualitative-analytical methodology, combining theories from applied linguistics, semiotics (particularly Barthesian models), and digital humanities. Through case studies involving AI-assisted interpretation of English and multilingual lyrics, it illustrates how mediated interaction with symbolic meaning fosters deeper cognitive engagement. Furthermore, the paper discusses the pedagogical implications of AI as a “mediating agent,” offering not only automated translation or vocabulary support, but also cultural and intertextual annotations that support learners' interpretive autonomy. Ultimately, this interdisciplinary study argues that the convergence of SLA, semiotics, and AI opens new pedagogical pathways. It reframes AI not merely as a technological aid but as a semiotic bridge that connects learners to the layered meanings of language, culture, and identity expressed through music.