Africa · DR Congo

French (African) conversational speech dataset

2,000 hours of spontaneous French (African) conversations recorded in the DR Congo across 200 vetted native speakers. Dual-channel audio with time-aligned transcripts, speaker metadata (age, gender, region, device), and full chain-of-consent documentation. Licensed for commercial ASR, TTS, and voice AI training.

Dataset specifications

LanguageFrench (African)
Recorded inDR Congo
Speech typeSpontaneous two-person conversations
Volume2,000 hours
Speakers200 vetted native speakers
AudioDual-channel (one channel per speaker)
TranscriptsTime-aligned, human-verified
MetadataAge, gender, region, recording device
LicenseCommercial (training & evaluation)
Price$65 per hour of audio

Need more hours, another dialect or your own recording setup? We collect speech data to spec.

Built for

Training and evaluating speech models that must handle real French (African) speech:

  • Automatic speech recognition (ASR / STT)
  • Text-to-speech & voice synthesis prosody
  • Voice agents and IVR for the DR Congo
  • Speaker diarization & turn-taking models
  • Speech LLM / audio-understanding fine-tuning

Why conversational data?

Models trained on read speech consistently underperform on spontaneous audio. Disfluencies, overlap, and natural speech rates aren’t in the training distribution. This dataset closes that gap for French (African). Read more in our guide to conversational vs. scripted speech data.

Free samples

Audit the French (African) data yourself

Share your company email and we’ll email you representative audio, matching transcripts, and the metadata schema. Check audio quality, transcript accuracy, and speaker diversity before you spend a dollar.

Please use your company email. We’ll reach out shortly with samples.

Public alternatives

Public Congolese French speech data vs. this dataset

SourceWhat it isLicenseCommercial training
Mozilla Common Voice French (Scripted and Spontaneous Speech) (opens in a new tab)Mozilla Common Voice (via Mozilla Data Collective)French sentences read by volunteers, not Congo-specific; a Spontaneous Speech release adds unscripted answers.CC0 1.0Allowed

None of the free French data listed here is specific to DR Congo; this dataset is two-person conversation recorded in DR Congo.

Licenses as published by each source, checked October 2026. Check the current terms before use.

FAQ

Frequently asked questions

What does the French (African) speech dataset include?

2,000 hours of spontaneous two-person conversations from 200 vetted native speakers recorded in the DR Congo, delivered as dual-channel audio with time-aligned transcripts, speaker metadata (age, gender, region, device), and consent documentation.

What makes Congolese French hard for speech recognition?

French in the DR Congo is spoken alongside Lingala, Swahili, Kikongo and Tshiluba, and everyday conversation mixes them freely. Pronunciation, rhythm and vocabulary differ from Parisian French, so models trained on European French lose accuracy with Central African speakers.

Is there free Congolese French speech data?

None specific to the DR Congo, but Mozilla Common Voice French is free for commercial use. This dataset is spontaneous two-person conversation recorded in the DR Congo, with speaker metadata, one channel per speaker and signed commercial-use consent.

Can I use this French (African) dataset commercially?

Yes. The dataset is licensed for commercial use, including training ASR, TTS, and other voice-AI models. Every speaker has signed explicit commercial-use consent, and we provide the full consent chain for your legal review.

How much does the French (African) speech dataset cost?

Pricing is $65 per hour of audio. Volume discounts are available for full-dataset and multi-language purchases. Contact us for a quote.

Can I evaluate samples before buying?

Yes. Request samples with your company email, and we'll email you representative audio files and matching transcripts so your team can audit quality before committing.

Related datasets

You might also need

Compare all 9 African datasets by hours, speakers and price.