How Does Stream Translation Work?

Stream translation works by capturing microphone audio, converting it to text via speech recognition, translating to the target language, and displaying subtitles on stream via OBS browser source — all in under 2 seconds.

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The Stream Translation Pipeline

Modern stream translation tools like StreamTranslate use a four-stage pipeline: audio capture → speech recognition → machine translation → subtitle display. Each stage is optimized for minimum latency.

Stage 1: Audio capture. The browser source captures your microphone audio in real time. No software install needed — it runs in the browser.

Stage 2: Speech recognition (STT). Audio is sent to a speech-to-text engine. StreamTranslate uses Deepgram Nova-2, which processes audio in chunks of ~500ms and returns accurate transcriptions even for accents and gaming audio.

Stage 3: Machine translation. The transcribed text is sent to a translation API. StreamTranslate uses a multi-provider translation race — it simultaneously queries multiple translation engines and uses the first result that returns, minimizing latency.

Stage 4: Subtitle display. The translated text is rendered as a styled subtitle overlay displayed via the OBS browser source. The entire pipeline completes in under 2 seconds end-to-end.

Frequently asked questions

How does stream translation work technically?
Stream translation captures microphone audio, sends it to a speech recognition engine (STT), translates the transcribed text using machine translation, and displays the result as a subtitle overlay on the stream via OBS browser source — all in under 2 seconds.
What speech recognition does StreamTranslate use?
StreamTranslate uses Deepgram Nova-2 for speech recognition, one of the most accurate commercial STT engines available, with a word error rate under 7% for English — significantly better than browser-based alternatives.
How fast is real-time stream translation?
StreamTranslate achieves under 2-second latency end-to-end from when the streamer speaks to when the translated subtitle appears on stream. This is fast enough to keep up with normal conversational speech.

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