Transcription vs Translation: The Difference

BrassTranscripts transcribes audio, which means it keeps the spoken language and turns speech into text; translation is the separate task of converting that text into a different language. Transcription (speech to text, same language) and translation (one language to another) are two distinct steps, and a transcription service returns text in the language the speaker actually used. If you record a Spanish interview, BrassTranscripts gives you a Spanish transcript — getting English out of it is a second, downstream step.

Confusing the two is one of the most common mistakes people make when buying transcription. This guide draws a clean line between the tasks, explains why the distinction matters for accuracy and cost, and shows the exact workflow for getting an English document out of non-English audio.

Quick Navigation

• Transcription vs Translation: The Core Difference
• Why the Two Tasks Get Confused
• What the SeamlessM4T Research Shows
• What BrassTranscripts Actually Does
• How to Get an English Transcript of Non-English Audio
• Choosing the Right Task for Your Project
• Frequently Asked Questions
• About BrassTranscripts

Transcription vs Translation: The Core Difference

Transcription converts spoken audio into written text in the same language, while translation converts text from one language into another — BrassTranscripts performs the first task and returns a transcript in the language that was spoken. The two operations sit at different points in a language pipeline: transcription changes the medium (sound to writing) but not the language, and translation changes the language but not the medium (text stays text).

A concrete example makes the boundary obvious. A one-hour German podcast episode goes through transcription and comes out as a German text document — every word the hosts said, written down in German. If you then want that document in English, you run it through translation, which rewrites the German text as English text. Two separate tasks, two separate outputs: a German transcript and, optionally, an English translation of it.

The distinction is not pedantic. Transcription accuracy and translation accuracy are measured differently, priced differently, and fail differently. A transcription error means a word was misheard; a translation error means a correctly-heard word was rendered wrong in the target language. Keeping the steps separate lets you verify each one on its own terms.

Why the Two Tasks Get Confused

People conflate transcription and translation because both involve turning speech into a readable document across a language barrier, but BrassTranscripts treats them as distinct stages with different tools and different success criteria. The confusion usually surfaces when someone uploads Spanish audio and expects an English file back — they wanted the end-to-end result and assumed one service did the whole journey.

Marketing language adds to the muddle. Some tools advertise "transcribe in any language" and "translate your meetings" in the same breath, blurring where one task ends and the next begins. The honest framing is that a transcription engine's job is to hear accurately, and a translation engine's job is to convert meaning between languages — different problems that happen to appear side by side in multilingual workflows.

There is also a technical reason the tasks are separate. Speech recognition has to handle acoustics: accents, background noise, overlapping speakers, and crosstalk. Translation operates on clean text and has to handle idiom, grammar, and cultural nuance. Bolting them together in one pass can compound errors, which is why keeping transcription and translation as discrete steps often produces a cleaner final document.

What the SeamlessM4T Research Shows

SeamlessM4T is a research model that demonstrates how far combined speech tasks have come, but it also illustrates that transcription and translation remain distinct capabilities inside a single system rather than one blended operation. In the paper "SeamlessM4T: Massively Multilingual & Multimodal Machine Translation," the Seamless Communication team at Meta AI (2023) describes a single model that handles automatic speech recognition, speech-to-text translation, and speech-to-speech translation across roughly 100 languages (arxiv.org/abs/2308.11596).

The research is notable for scale and measured gains. SeamlessM4T was trained on about 1 million hours of speech, and on the FLEURS benchmark it improved direct speech-to-text translation by 20% BLEU over the prior state of the art, while proving more robust to background noise and speaker variation. Those numbers describe translation performance specifically — the speech-to-text translation task — which is a different capability from plain speech recognition (transcription) even inside the same model.

The takeaway for buyers is the important part. Even the most advanced multilingual research systems list speech recognition and translation as separate functions, because they answer separate questions: "what did the speaker say?" versus "what is that in another language?" SeamlessM4T is external research from Meta AI and is not the technology BrassTranscripts runs; it is cited here to show that the field itself treats transcription and translation as distinct tasks.

What BrassTranscripts Actually Does

BrassTranscripts is a transcription service — it converts speech to text in the language that was spoken and returns that transcript, using advanced AI transcription with automatic speaker identification. It does not translate. Upload French audio and you get a French transcript; upload Japanese audio and you get a Japanese transcript. The service detects the language automatically and transcribes in it.

The output is built for the spoken-language document: automatic speaker labels so you can see who said what, and four formats — TXT, SRT, VTT, and JSON — covering plain reading, subtitles, and structured data. All of that describes the transcript itself, in the original language. None of it changes the language of the words.

This is a deliberate scope. Doing one task well — accurate speech-to-text with speaker identification across 99+ languages — is different from trying to be a translation engine too. When you need translation, dedicated translation tools do that job well, and pairing them with an accurate transcript gives better results than a single tool attempting both at once. For a deeper look at how modern systems reach this many languages, see the multilingual speech research overview and the explainer on how AI transcription scaled to 100 languages.

How to Get an English Transcript of Non-English Audio

To turn non-English audio into an English document, transcribe in the source language first and translate the text as a second step — BrassTranscripts handles the transcription, and a translation tool handles the conversion. Running the steps in this order gives the translator clean, accurate text to work from instead of asking one system to hear and translate simultaneously.

The workflow is three moves:

1. Transcribe in the source language. Upload your audio to BrassTranscripts. It detects the language and returns a transcript in that language — Spanish audio produces a Spanish transcript, complete with speaker labels. Download it as TXT for the easiest handoff to a translator.
2. Translate the text. Paste the transcript into a dedicated translation tool such as DeepL or Google Translate, or a large language model, to produce English text. Because you are translating clean written text rather than raw audio, the translator has the best possible input.
3. Review the result. Spot-check the English against the source transcript, especially names, numbers, and technical terms. Because you kept the original-language transcript, you always have a reference to verify against — something you lose if a single tool converts audio straight to English.

This two-step method is more accurate and more transparent than a one-shot audio-to-English conversion, and it works for any language pair. For a full worked example, see the Spanish audio to English text guide, and for language coverage details, the non-English transcription guide.

Choosing the Right Task for Your Project

Choose transcription when you need a written record in the spoken language, and add translation only when the audience reads a different language — BrassTranscripts covers the transcription half of that decision for 99+ languages. Most projects need transcription first regardless, because an accurate source-language transcript is the foundation everything else builds on.

Reach for transcription alone when the speaker and the reader share a language: meeting minutes for a same-language team, subtitles in the original language, searchable archives, or content repurposing. Add a translation step when you are localizing subtitles, sharing an interview with an international audience, or producing a document for readers who do not speak the source language. In every one of those cases, the sequence is the same — transcribe, then translate.

If terminology is tripping you up, the AI transcription glossary defines transcription, translation, ASR, and the other terms that get used interchangeably. Knowing which task you actually need is the difference between one clean upload and a frustrating round of re-work.

Frequently Asked Questions

What is the difference between transcription and translation?

Transcription converts speech to text in the same language the person spoke — Spanish audio becomes Spanish text. Translation converts text from one language into another — Spanish text becomes English text. BrassTranscripts performs transcription, returning text in the spoken language, and translation is a separate downstream step.

Does BrassTranscripts translate audio into English?

No. BrassTranscripts transcribes audio into text in the language that was spoken. If someone speaks French, BrassTranscripts returns a French transcript. To get English text from French audio, transcribe first, then run the French transcript through a translation tool as a second step.

Can one AI model do both transcription and translation?

Some research models combine both tasks. Meta AI's SeamlessM4T (2023) handles speech recognition and speech-to-text translation across roughly 100 languages in a single system. BrassTranscripts focuses on transcription — accurate speech-to-text in the spoken language — and does not translate.

How do I get an English transcript of non-English audio?

Use two steps. First, transcribe the audio in its source language with BrassTranscripts to get accurate text. Second, paste that transcript into a translation tool such as DeepL or Google Translate to produce English. Transcribing in the source language first gives the translator cleaner input and a better result.

Which languages does BrassTranscripts transcribe?

BrassTranscripts transcribes 99+ languages with automatic language detection, returning text in whichever language was spoken. It does not convert between languages — that is translation, a separate task handled by dedicated translation tools.

About BrassTranscripts

BrassTranscripts is a professional AI transcription service offering automatic speaker identification, support for 99+ languages with automatic language detection, and four output formats (TXT, SRT, VTT, JSON) with every transcription. Files are priced per batch with no subscription — $2.50 for files up to 15 minutes and $6.00 flat for files 16 minutes and longer at any length. Remember that BrassTranscripts returns text in the spoken language; translation to another language is a separate downstream step. Start transcribing in about 30 seconds.