Speaking in Terms of Money: Financial Knowledge Acquisition via Speech Data Generation

Abstract

Earning a living often leaves low-income individuals with little time for learning new skills, perpetuating a cycle where the need for immediate income restricts access to learning. In this study, we investigate if digital work, specifically speech data generation, can facilitate domain-specific knowledge acquisition. For the purposes of this study we focus on finance and banking. We conducted a two-week financial literacy program with low-income individuals (n=55) in Wagholi, a semi-urban area in Pune, India. Participants read aloud and recorded a nine-lesson financial curriculum, earning ₹2000 (≈ $24) for ≈ 90 minutes of voice-recording. By conducting pre- and post-tests, we found a significant increase in participants’ financial knowledge with a high effect size (cohen’s d = 1.32) and medium normalised score gain (hake’s g = 0.58). Fourteen follow-up interviews indicated the work was accessible and conveniently integrated into participants’ daily lives. Additionally, the program triggered attitude change among participants and community dialogue about critical financial concepts. Our results suggest that digital work can become an effective method for knowledge acquisition and should be tested at a larger scale.