Lagos-concentrated, so co-located with the buyers. Absent from ElevenLabs TTS, AWS Transcribe and Google Chirp 3; ElevenLabs' own published STT band for it is 25–50% WER.
- yor
- Tonal
- 7 dialects
49 AI readiness
46m
Extremely low-resource
40m
speakers, low confidence estimate
31
AI readiness, weighted toward speech
3
dialects tracked as separate collection targets
Kinshasa is one of the largest cities on the continent and francophone Central Africa is served by essentially nobody. The pivot language here is French, which is a different pipeline from every English-pivot row above it.Overwhelmingly second-language speakers, which is what makes the range so wide — 20m to 40m depending entirely on where the threshold for 'speaks Lingala' is set.
Capability coverage
Under ten hours, benchmark-only presence. Collection required before anything ships.
The facts
Dialects
Dialect is self-declared at contribution and then validated against gold-standard clips. Which dialects people turn up to record in is a better demand signal than any desk ranking.
Open corpora that cover it
Voices
No voice yet. Studio recording is the scarcest asset in this whole field — the largest open African corpus holds 11,000 hours and about twenty of them are studio-grade — so voices follow demand rather than leading it.
Same family
Related
A Yoruba model helps Igbo less than the shared border suggests, and a Hausa model transfers usefully across Chadic languages in three other countries. These share Niger–Congo with Lingala.
Lagos-concentrated, so co-located with the buyers. Absent from ElevenLabs TTS, AWS Transcribe and Google Chirp 3; ElevenLabs' own published STT band for it is 25–50% WER.
49 AI readiness
46m
Commercially dense in trade and diaspora remittances. Absent from AWS Transcribe entirely and capped at Chirp 2 on Google.
49 AI readiness
33m
The highest-value regional asset after Hausa: cross-border into Niger, Cameroon and Chad, with strong humanitarian and agricultural demand.
18 AI readiness
20m±
Take an API key and make the call from your own code, or start in the playground and see what the model actually does with your text.