Building Community-Centred NLP Resources for Puno Quechua
It addresses the lack of digital tools for Quechua speakers, providing foundational resources for a highly under-resourced language.
The paper presents the first dedicated ASR resources for Puno Quechua, including a 66-hour speech corpus and systematic benchmarks, achieving competitive results with fine-tuned models like Whisper-base.
The preservation of under-resourced languages requires digital tools and resources shaped by and for their speakers. We present the first dedicated ASR resources for Puno Quechua (ISO 639-3: qxp): (1) the largest speech corpus for any single Quechua variety, consisting in 66 hours of recordings for scripted and spontaneous speech (including 36 hours of manually transcribed and validated data), collected via a participatory design campaign; (2) the first systematic ASR benchmark for Puno Quechua, evaluating state-of-the-art models and fine-tuning Whisper-base, wav2vec2-base, and XLS-R-300M, with and without continued pre-training (CPT); (3) an open release of all datasets and fine-tuned models.