Use LiveKit Agents transcription when you need to transcribe audio in a LiveKit room as part of a realtime voice-agent pipeline. Use Flutter’s speech_to_text package for short, user-initiated phrases recognized through the device’s speech-recognition capability. They work at different architectural layers, so they are not interchangeable plugins.
What is the difference?
LiveKit Flutter is a client SDK for joining a LiveKit room and handling realtime audio, video, and data. Speech recognition for a voice-agent workflow belongs to LiveKit Agents, which processes audio in the agent pipeline. LiveKit documents Agents runtimes for Python and Node.js; it is not a Dart or Flutter transcription framework.
By contrast, Flutter’s speech_to_text package exposes the speech-recognition facilities provided by the underlying device platform. Its maintainers describe it as suited to commands and short phrases, not continuous transcription or always-on listening.
Which option fits your use case?
| Decision point | LiveKit Agents STT | Flutter speech_to_text |
|---|---|---|
| Audio being recognized | Audio handled in a LiveKit room and voice-agent pipeline. LiveKit Agents STT documentation | Audio recognized through the device platform’s speech facility. Package documentation |
| Best documented use | Realtime voice-agent transcription delivered to room clients. Agents documentation | Short user commands or phrases, such as a quick request after tapping a microphone button. Package documentation |
| Continuous room conversation | A suitable architecture to investigate when you configure a supported STT model or provider and deliver transcript updates to the Flutter UI. Agents documentation | Not intended for continuous or always-on transcription. Package documentation |
| Provider operations | LiveKit Inference manages provider usage and rate limits through LiveKit Cloud; provider plugins allow you to manage provider billing and credentials. LiveKit Agents STT documentation | Uses the device platform’s recognition capability; behavior and capabilities vary by platform. Package documentation |
| Documented platform coverage | The Flutter client docs list Android, iOS, web, macOS, Windows, and Linux; Agents documentation identifies Python and Node.js runtimes. LiveKit documentation | The package docs list Android, iOS, macOS, web, and Windows, with Windows support marked beta. Linux support is not listed. Package documentation |
How a LiveKit transcript reaches a Flutter client
When an AgentSession performs speech-to-text, LiveKit Agents can publish transcription to frontend clients in realtime. The current frontend integration uses text streams with the topic lk.transcription; transcript streams include the lk.transcribed_track_id attribute. See the LiveKit Agents frontend guide for the current integration path.
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Streams may contain interim and final segments. Use the final indicator to replace or finalize the displayed interim text rather than treating every update as a new utterance. Interim and final streams share segment identifiers, so logging each update as a separate transcript can make the same speech appear duplicated.
Older tutorials may show the TranscriptionReceived client event or publish_transcription() method. LiveKit marks both as deprecated in favor of the current text-stream approach. The Flutter API also documents a server TranscriptionEvent containing a participant, an optional track publication, and transcript segments, with attributes for segment ID, transcribed track ID, and whether a segment is final or interim. Check the API for the exact livekit_client version pinned by your app: the cited reference pages cover different package versions, 2.11.0 and 2.12.0. Frontend guide · Flutter client API reference
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Choose the transcription architecture
For audio already flowing through a LiveKit room
If your app publishes microphone audio to a LiveKit room and needs ongoing conversation transcription, use the Agents STT route: configure a supported model or provider in the agent pipeline, then consume the published text stream in the Flutter client. The Flutter SDK handles the room connection; the agent pipeline performs the transcription.
For an occasional phrase triggered by the user
If the interaction is a short utterance initiated by a user action—such as tapping a button to dictate a quick command—speech_to_text is a reasonable Flutter-level option. Its documented scope does not extend to continuous room transcription or always-on listening.
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For control over provider credentials and billing
Within LiveKit Agents, choose between LiveKit Inference and a provider plugin according to who should manage the provider relationship. Inference is managed through LiveKit Cloud, where the documentation says a separate provider API key is not required and usage and rate limits are managed by LiveKit. A plugin is the alternative when you want to manage provider billing and credentials or use a provider or model not served through Inference. This describes an operational boundary, not proof that one option is always cheaper, faster, or more accurate. LiveKit Agents STT documentation
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What to verify before choosing
- Where the audio goes: establish whether recognition should happen in the LiveKit agent pipeline or through the device’s platform speech service.
- How often recognition runs: distinguish ongoing room conversation from brief, user-started commands.
- How the UI handles updates: for LiveKit text streams, use segment identifiers and the final/interim state to update transcript text without duplicating it.
- Platform and version support: check the current package documentation and the operating-system versions your app supports. In particular, the
speech_to_textpackage marks Windows support beta and does not list Linux. - Operational ownership: decide whether LiveKit Cloud should manage inference usage and rate limits, or whether your team should manage a provider plugin’s credentials and billing.
- App-specific performance and policy: test the exact provider or device combination for latency, accuracy, privacy and cost before making comparative claims. The cited documentation does not establish a universal winner on these measures.
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