Despite major advances in information retrieval (IR) and language technologies, speakers of extremely low-resource ethnic community languages (ECLs) remain largely excluded from digital information access. With Tanzania having over 120 languages, yet most IR systems and digital assistants primarily support English and, to a limited extent, Kiswahili. This disproportionately affects rural populations (over 65%), where ECLs are used alongside Kiswahili in daily life. This paper presents the ongoing Ethnic Voices initiative, which addresses this gap by building foundational text and speech resources explicitly relevant to IR research in extremely low-resource multilingual settings. The project targets six ECLs in Tanzania, with current data collection completed for Hehe and Luguru. Data collection from the two ECLs has produced over 800 Kiswahili-ECL parallel sentences per language and over 95 hours of speech. Preliminary survey results show strong demand for multilingual and voice-based access to information. It further identifies language barriers as a primary limitation of existing English-centric IR systems. This also paper discusses the IR implications of these findings and outlines directions toward inclusive retrieval and evaluation in extremely low-resource languages. Beyond resource creation, we position the collected dataset as IR-enabling infrastructure that supports the formulation of retrieval tasks, the development of baseline systems, and the design of evaluation protocols in benchmark-scarce, extremely low-resource multilingual settings.