Otter adds 27 languages and prepares transcription for meetings that switch languages

When a team starts a call in English and then switches to Russian, the transcription service has to handle two tasks at once: recognize the speech and detect that the language has changed. A mistake in the second task can derail the entire next section of the transcript. Otter has announced a feature designed to detect these switches automatically and keep transcribing without anyone manually changing the settings.

The company is also expanding language support, adding 27 languages to the four it already offers. Once the rollout is complete, the total will be 31. For international product teams, this is a reason to test whether a single service can cover more of their work meetings. But it is important to distinguish between languages that are already available and the promised ability to handle conversations that switch languages on the fly.

What is available now, and what is still to come

According to TechCrunch, 13 new languages are already available: Mandarin Chinese, Korean, German, Italian, Cantonese, Portuguese, Russian, Indonesian, Malay, Dutch, Turkish, Vietnamese and Polish. Russian transcription is therefore part of the first wave of the expansion.

The company promises to add another 14 languages later. These include Arabic, Hindi, Hebrew, Thai, Persian, Czech and several Scandinavian languages. The material provided gives no specific deadline for completing the rollout.

Automatic language-switch detection is also described as an upcoming feature. Headlines about conversations in more than 30 languages therefore need a careful reading: the platform's eventual language coverage does not mean that every announced feature is already available to every user.

The new languages use Otter's own speech recognition models. The company said it trained them on publicly available datasets, with native speakers volunteering to review transcripts. That describes the development process, but does not in itself show how well the service handles particular workplace conversations.

What this looks like on a typical call

Imagine a meeting of a distributed team. A product manager discusses a launch in English, a developer clarifies technical constraints in Russian, and a colleague from Brazil responds in Portuguese. Otter's intended approach is for the service to detect each switch automatically and keep transcribing. Participants would not have to interrupt the discussion to change the language in the settings.

The practical value lies in preserving the substance of the meeting. If the service misses the developer's clarification, someone reading the transcript later may overlook an important launch constraint. For a team that refers back to transcripts when assigning tasks, the quality of these passages matters directly.

Multilingual transcription, however, is not the same as translation. The announcement concerns recognizing a conversation as its languages change. It provides no basis for promising that every contribution will automatically appear in a single selected language. If employees need a unified set of meeting notes in Russian or English, that capability should be checked separately.

What to check before switching

The material contains no numerical accuracy metrics, independent comparison with competitors or results for conversations that mix languages. It also does not explain how the feature handles accents, overlapping speech, specialist terminology or brief foreign-language phrases within a sentence. These are precisely the cases worth including in a test recording.

A developer or product manager should take several typical team meetings and check specific details: whether product names, numbers, deadlines and the wording of decisions survive a switch to another language. A transcript's overall readability does not guarantee that it is usable for subsequent work.

Otter is also developing tools that build on meeting history: Work Mode gathers context before a call, while Live Assist offers suggestions during the conversation. This makes the quality of the underlying transcript particularly important: a missed contribution may be left out of the context used for subsequent work.

Teams that need transcription in Russian or other languages in the first wave already have a reason to try the update. The decision to move all international calls to the service is best made after testing automatic language switching on their own conversations, once the feature becomes available.