Turn South African audio
sisään English you trust.

A different approach to South African English translation.

South African English is one of the country’s 11 official languages, shaped by a colonial and apartheid-era history that folded in Afrikaans, Zulu, Xhosa, and dozens of other influences. It carries its own vocabulary, rhythm, and pronunciation: “braai” for barbecue, “robot” for traffic light, “takkies” for sneakers. Mutually intelligible with other English variants, but different enough that a literal, word-for-word tool misses what a caller, candidate, or interviewee actually meant.

Why generic translation tools miss the mark

For most teams, translating South African English audio meant a transcript full of guesses. Regional pronunciation confused speech-to-text engines. Local idioms and code-switching between English and Afrikaans or Zulu got flattened into nonsense, or dropped entirely. A researcher or recruiter was left replaying the file, translating by ear, and hoping they caught the names and numbers correctly.

Reading the recording, not just guessing at words

Speak AI treats every South African English recording the way a bilingual analyst would, at machine speed. Each file is transcribed in your language, with 100+ supported, and Speak AI selects the speech and translation model best suited to the accent and terms in the file rather than forcing every recording through one engine. Then the translation carries meaning across, not just words: local terms are rendered into their plain English equivalent, and the tone, pacing, and emphasis of the speaker are read alongside the transcript so nuance is not lost. Names, dates, and reasons for the call are extracted into structured fields your systems can use.

Then the questions start. Ask across your entire South African English library with AI chat, using the same high-quality prompt workflows teams once stitched together manually, now running natively over your recordings with ChatGPT, Claude, and Gemini built in.

What teams ask their translated recordings

• “Translate this interview and flag any local terms you weren’t sure about.”
• “Which calls this month mention pricing, and what exactly did the caller say in English?”
• “Show me every recording where the speaker switched between English and Afrikaans.”
• “Which candidates sound most confident, based on tone as well as the translated words?”
• “Summarize the common themes across all interviews this quarter, in English.”

From a pile of recordings to a searchable English library

The result is a South African English archive that reads like it was recorded in English from the start. Terms and idioms carry across instead of getting lost. Names, numbers, and outcomes land in your CRM through automations instead of a note scribbled after playback. Trends across hundreds of interviews or calls become a report instead of a guess, and dashboards you can customize and white-label track translation volume, sentiment, and themes over time, so this quarter is measured against last. One education group used embedded recorders and Speak AI to scale multilingual assessment across languages, without adding headcount.

And because translation rarely lives alone, the same engine scores calls, interviews, and meetings on your own criteria, connecting South African English recordings to call scoring ja coaching across every conversation your team has.