Turn Swahili audio
dans texte que vous pouvez rechercher.

A different approach to Swahili transcription.

Le swahili, ou kiswahili, est parlé par plus de 100 millions de personnes à travers le Kenya, la Tanzanie, l'Ouganda, le Rwanda, le Burundi et la République démocratique du Congo, et il a le statut officiel dans l'Union africaine. Son vocabulaire porte les traces de siècles de contact entre les locuteurs bantous, arabes, persans, et plus tard portugais et anglais le long de la côte d'Afrique de l'Est, et il reste l'une des langues à la croissance la plus rapide sur Internet. Transformer la parole swahilie en texte utilisable a généralement signifié un transcripteur bilingue travaillant ligne par ligne, ou un outil générique qui bien exécute les mots faciles et massacre le reste.

Where Swahili transcription usually breaks down

Most transcription engines are tuned for a small set of high-resource languages, and Swahili is rarely one of them. Loanwords from Arabic and English get flattened, pronunciation that shifts across Kenya, Tanzania, and Uganda gets misheard, and the tone behind a frustrated customer call or an urgent field report never survives into the transcript. Teams end up re-listening to the recording anyway, which cancels out most of the time transcription was supposed to save.

Lire l’enregistrement, pas seulement les mots

Speak AI transcribes Swahili audio and video with speaker labels and timestamps, then analyzes the recording itself: the tone and energy behind a customer complaint, the urgency in a field call, the confidence in a market research interview. Names, locations, and callback details are extracted into structured fields your team can search. Then you can ask across your entire Swahili archive with AI chat, using ChatGPT, Claude, and Gemini built directly into the workspace.

• Swahili audio and video, transcribed with speaker labels and translation into English or another language.
• Handles regional variation across Kenya, Tanzania, Uganda, and the wider East African coast, alongside standard written Swahili.
• Captions and subtitles (SRT, VTT) generated straight from the timestamped transcript.
• Export to Word, PDF, TXT, CSV, or JSON, depending on how your team needs to use it.

D’une pile d’enregistrements à une archive consultable

The result is a Swahili archive that behaves like a well-run English one. Customer calls, focus groups, and field interviews become searchable text instead of a folder of audio nobody has time to relisten to, and des tableaux de bord que vous pouvez personnaliser et mettre en marque blanche track sentiment and themes across your Swahili recordings over time. One multilingual education platform put its assessment recordings through this kind of workflow across embedded recorders spanning multiple languages, without hiring reviewers for each one.

And because Swahili recordings rarely live in isolation from the rest of your work, the same engine scores calls and coaches teams on the same criteria, connecting Swahili transcription to évaluation des appels and the wider base de connaissances your team already runs on.