Transcription vs Translation

These two terms are frequently confused, but they describe fundamentally different tasks. Transcription is the process of converting spoken audio into written text in the same language. Translation is the process of converting meaning from one language into another. A Yoruba interview that is transcribed produces written Yoruba text. That same interview translated produces text in, say, English or French.

Where the confusion arises

The overlap happens because many real-world workflows involve both steps. A journalist records an interview in Hausa, needs a written Hausa transcript for their records, and also needs an English version for an international publication. Some tools bundle these steps together, which blurs the line. But technically, each step relies on different technology: transcription leans on acoustic and language models tuned to a specific language, while translation relies on neural machine translation models trained on parallel text corpora.

Why the distinction matters for African languages

Getting transcription right is a prerequisite for accurate translation. If the ASR system misrecognises a Swahili word because of tonal ambiguity or background noise, that error cascades into the translation. This is why AuTrans focuses first on delivering high-quality transcription, the foundation has to be solid before any downstream task can succeed.

The distinction also affects how users should evaluate output. A transcription error means the system heard the wrong word. A translation error means the system understood the word but expressed it incorrectly in the target language. Knowing which type of error you are looking at helps you troubleshoot more effectively.

Practical impact

AuTrans provides transcription as its core service, converting speech in supported African languages into accurate written text. Translation capabilities can then build on top of that clean transcript, whether through integrated features or external tools, giving users a complete pipeline from spoken word to multilingual text.