  This paper describes foundational efforts with SautiDB-Naija, a novel corpus
of non-native (L2) Nigerian English speech. We describe how the corpus was
created and curated as well as preliminary experiments with accent
classification and learning Nigerian accent embeddings. The initial version of
the corpus includes over 900 recordings from L2 English speakers of Nigerian
languages, such as Yoruba, Igbo, Edo, Efik-Ibibio, and Igala. We further
demonstrate how fine-tuning on a pre-trained model like wav2vec can yield
representations suitable for related speech tasks such as accent
classification. SautiDB-Naija has been published to Zenodo for general use
under a flexible Creative Commons License.
