REVIEW 1 cited by
Towards Afrocentric NLP for African Languages: Where We Are and Where We Can Go
Not yet reviewed by Pith; the record is open.
This paper has not been read by Pith yet. Machine review is queued; the pith claim, tier, and objections will appear here once it completes.
SPECIMEN: schema-true, not a live event
T0 review · schema-true
One-sentence machine reading of the paper's core claim.
pith:XXXXXXXX · record.json · timestamp
Signed reviews
read the original abstract
Aligning with ACL 2022 special Theme on "Language Diversity: from Low Resource to Endangered Languages", we discuss the major linguistic and sociopolitical challenges facing development of NLP technologies for African languages. Situating African languages in a typological framework, we discuss how the particulars of these languages can be harnessed. To facilitate future research, we also highlight current efforts, communities, venues, datasets, and tools. Our main objective is to motivate and advocate for an Afrocentric approach to technology development. With this in mind, we recommend \textit{what} technologies to build and \textit{how} to build, evaluate, and deploy them based on the needs of local African communities.
Forward citations
Cited by 1 Pith paper
-
Amplify Initiative: Building A Localized Data Platform for Globalized AI
Amplify's pilot with 155 experts produced an annotated dataset of 8,091 adversarial queries in seven languages, intended to evaluate AI safety and cultural relevance in Sub-Saharan Africa.
Discussion (0). Continue with ORCID to comment.