A localization manager who runs prerecorded dubbing has time on their side: transcripts get reviewed, translations get corrected, synthesized audio gets QC'd before anyone hears it. A live broadcast removes all of that. When a match kicks off or a keynote starts, localized audio has to exist within moments of the original speech, in every language your audience expects, with no chance to fix a bad segment after the fact.
That constraint is why live events have historically defaulted to human simultaneous interpreters, expensive, hard to schedule, and rarely available across a wide language slate for a single event. Live AI dubbing changes the cost and coverage math, but it also changes the operating model. It is not a file you upload; it is a stream you run. This guide walks through how Ollang's Live Dubbing product works in production terms, how feeds get in, how localized audio comes back, and how you monitor and plan around it, so you can evaluate it the way you would any other piece of broadcast infrastructure.
How Live AI Dubbing Differs From Prerecorded Localization
Ollang's prerecorded dubbing pipeline is built around control points: source assets and reference materials go into a project, an AI dubbing order runs transcription, translation, and voice synthesis, and human reviewers can edit dialogue, adjust pacing, and trigger segment-level resynthesis before delivery. Every step tolerates delay because the audience has not seen the content yet.
Live Dubbing collapses that pipeline into a continuous stream. Per Ollang's documentation, the workflow ingests a microphone or broadcast feed, streams the speech to Ollang's edge network, dubs it into the target language, and returns localized audio to viewers, with an advertised sub-second end-to-end latency.
Two operational consequences follow from that design:
- There is no review gate. The quality controls you rely on for prerecorded work, glossaries, reviewer assignment, resynthesis, cannot sit between the speaker and the audience in a sub-second loop. Quality assurance shifts from correcting output to preparing input: rehearsing with real commentary, testing terminology-heavy speech before air, and validating each language pair in advance.
- Latency is the primary spec. In prerecorded dubbing, turnaround is measured in project time. In live dubbing, it is measured in the gap between the original speech and the localized audio. Sub-second latency, Ollang's stated figure for the live product, matters most when localized audio plays alongside live video or a live venue feed, where a multi-second lag is immediately obvious to viewers. As with any vendor latency claim, measure it yourself under your own network conditions during a pilot; end-to-end figures depend on your encoder, network path, and playback stack as well as the dubbing service.
Ingesting Microphone and Broadcast Feeds
Ollang supports two ingest paths for live feeds: WebRTC and RTMP. The choice maps cleanly onto the three use cases the product names, sports commentary, news, and live conferences.
WebRTC is the low-latency, browser-native path. It fits scenarios where the source is a microphone rather than a broadcast chain: a conference speaker on stage, a remote panelist, or a commentator working from a laptop. Because WebRTC runs without dedicated encoder hardware, it also lowers the setup burden for event teams that do not have a broadcast engineer on site.
RTMP is the standard contribution protocol for broadcast encoders and streaming production tools. If your sports or news feed already flows through an encoder or a production switcher, RTMP lets you push a copy of that feed to Ollang without changing your existing chain. For a localization manager coordinating with a broadcast operations team, this matters practically: you are asking them to add an output, not rebuild a workflow.
In either case, plan the audio you send deliberately. The cleaner the speech signal, commentator mic rather than the full program mix with crowd noise, for example, the better the conditions you give the recognition and synthesis stages. Confirm with Ollang how the service behaves with your specific feed configuration during testing; the public documentation describes the ingest protocols but not every audio-routing scenario.
Generating and Returning Localized Audio
Once speech reaches Ollang's edge network, it is dubbed into the target language and localized audio is returned to viewers. The product advertises 30-plus live language pairs, with custom-language support available on request.
For planning purposes, treat that number as a starting point, not a matrix. Two things to verify before committing to an event slate:
- Your specific pairs. "30+ pairs" tells you the scale of coverage, not whether your exact source-to-target combination is included. Confirm each pair you need, and ask about the custom-language path early if a required pair is not standard, custom support presumably takes lead time.
- Direction. A pair that works in one direction (say, English commentary into another language) is not automatically confirmed in reverse. Validate the directions you will actually broadcast.
On the delivery side, the returned localized audio is described as broadcast-oriented output. How you route it to viewers, as a selectable audio track in your player, a separate stream per language, or in-venue channels for a conference, is a decision for your distribution stack. Map that routing before the event, because it determines how many parallel dubbing sessions you need to run and monitor simultaneously.