Use LiveKit Agents transcription when you need to transcribe audio from an ongoing LiveKit room conversation and deliver it to clients in realtime. Use Flutter’s speech_to_text package for brief, user-initiated commands or phrases recognized through the device’s speech-recognition service. They work at different architectural layers, so the choice depends on where the audio comes from and whether listening is continuous.
How the two approaches differ
LiveKit Flutter (livekit_client) is a client SDK for joining a LiveKit room and handling realtime audio, video, and data. For a code-first voice-agent pipeline, LiveKit directs developers to LiveKit Agents: the framework that handles agent-side voice processing, including speech-to-text. LiveKit documents Agents for Python and Node.js; it is not a Dart or Flutter transcription framework.
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By contrast, Flutter’s speech_to_text package exposes speech-recognition capabilities provided by the underlying platform. The package is intended for commands and short phrases, not continuous transcription or always-on listening.
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Which should you choose?
| Decision | LiveKit Agents STT | Flutter speech_to_text |
|---|---|---|
| Audio source | Audio handled in a LiveKit room and voice-agent pipeline. | Audio recognized through the device platform’s speech service. |
| Best-fit task | Realtime transcription for room or agent conversations, with transcripts sent to room clients. | Short, user-triggered commands or phrases, such as a quick request after tapping a microphone button. |
| Continuous conversation | Suitable architecture to consider: configure a supported STT model or provider and send transcript updates to the Flutter UI. | Not designed for continuous or always-on transcription, according to the package maintainers. |
| Provider operations | LiveKit Inference manages usage and rate limits through LiveKit Cloud without a separate provider API key. A provider plugin gives the developer control of provider credentials and billing, and access to providers or models not served through Inference. | Uses the device platform’s speech-recognition capability; available behavior can vary by platform. |
| Documented platforms | LiveKit Flutter lists Android, iOS, web, macOS, Windows, and Linux. Agents documentation identifies Python and Node.js runtimes. | The package lists Android, iOS, macOS, web, and Windows; Windows support is marked beta. Linux speech support is not listed. |
How LiveKit Agents transcripts reach Flutter
When an AgentSession performs speech-to-text, LiveKit Agents publishes transcription to frontend clients in realtime. The current integration path uses text streams with the topic lk.transcription. Transcript streams include an lk.transcribed_track_id attribute, which identifies the transcribed track.
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A text stream can deliver interim and final segments. Use the final indicator to update or replace the interim text for that segment; treating every update as a new utterance can show duplicated text. Interim and final streams share segment identifiers, so logging both as separate utterances can also make logs appear duplicated.
LiveKit’s text-stream guide marks the older TranscriptionReceived client event and publish_transcription() method as deprecated. Older tutorials may still use them, so check the current guide rather than copying that integration unchanged.
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The Flutter client API also documents a server TranscriptionEvent containing a participant, an optional track publication, and transcript segments. Its transcription attributes include a segment ID, transcribed track ID, and final/interim indicator. API reference pages have surfaced different livekit_client versions, including 2.11.0 and 2.12.0, while the SDK overview lists a newer version. Verify the event and attributes against the exact version pinned in your app’s pubspec.lock.
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If the app already publishes microphone audio into a LiveKit room and needs transcripts of that conversation, use the Agents STT route rather than treating a Flutter package as the room’s transcription engine. The Agent processes audio in its pipeline and makes transcript updates available to room clients through text streams.
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Within Agents, choose between LiveKit Inference and a provider plugin based on operational control. Inference centralizes provider usage and rate-limit management through LiveKit Cloud. A plugin lets you manage provider credentials and billing, or select a provider or model that Inference does not serve. That distinction does not establish which option will be cheaper, faster, or more accurate for a particular app.
Choose speech_to_text for brief device-recognized input
If a user taps a control, speaks a short command, and expects the device to recognize it, speech_to_text is a plausible Flutter-level choice. It does not require building the LiveKit Agents transcription path for a short interaction that can be handled by the platform speech facility.
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Do not choose it on the assumption that it will continuously transcribe a room conversation: its maintainers state that continuous conversion and always-on listening are outside the package’s intended use. Platform coverage also differs, and Windows support is marked beta, so confirm support for the operating systems and versions your app targets.
What neither option proves on its own
The documented architecture and package boundaries do not establish a universal winner for latency, recognition accuracy, privacy, or cost. Those outcomes depend on the speech model or provider, device and operating system, geography, app configuration, and how audio and transcripts are handled. Measure the exact provider-and-device combinations your users will run before making comparative claims or choosing on those criteria.
Quick Recap
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