This paper presents the methodology and outcomes of building collaborative speech corpora in Mozilla Common Voice (MCV), focusing on the Galician case within Proxecto Nós. We describe the organization of voice collection campaigns –on-site events, student participation, Validatón marathons, and corporate collaboration– and analyze the results in MCV v22.0. While the dataset has achieved a modest scale, major gaps remain in metadata completeness and dialectal tagging, with implications for ASR performance. Drawing on our experience, we highlight effective strategies for engagement, such as transparent communication, cultural identification, and user-friendly tools. We conclude with lessons learnt for improving data representativeness, participant retention, and ethical governance. The observations are specific to the Galician case study but may inform similar efforts in other lesser-resourced languages.

This paper introduces Nos_Brais-GL, a new open-access high-quality Galician speech corpus designed for the development of neural Text-to-Speech (TTS) systems. Nos_Brais-GL contains approximately 18 hours of professionally recorded male speech and a carefully curated set of utterances selected to ensure linguistic variation and phonetic and prosodic richness. Beyond its immediate application in synthetic speech generation, Nos_Brais-GL exemplifies good practices in TTS corpus design for lesser-resourced languages, emphasizing methodological transparency, open licensing, and interoperability.