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For a local Home Assistant voice assistant, choose the host computer for speech recognition: Home Assistant recommends at least an Intel N100 or equivalent for Whisper Base, which handles open-ended speech. If you only need supported home-control phrases, Home Assistant Green or a Raspberry Pi 4 can run Speech-to-Phrase in under one second, with Piper providing local speech output. Add a separate microphone-and-speaker satellite for hands-free use in a room; it does not replace the host running Home Assistant and its speech services.
Choose hardware by the kind of speech recognition you need
The most important hardware choice is the computer running Home Assistant and its local speech services. Speech-to-text is the part that most changes the host recommendation: a focused recognizer is relatively light, while open-ended Whisper transcription calls for more computing power. Text-to-speech is a separate stage and, in Home Assistant’s documented setup, Piper is optimized for Raspberry Pi 4.
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| Use case | Supported starting point | What to expect |
|---|---|---|
| Supported home-control phrases on modest hardware | Home Assistant Green or Raspberry Pi 4, using Speech-to-Phrase and Piper | Home Assistant reports Speech-to-Phrase transcription in under one second on either device. It recognizes a known subset of commands rather than arbitrary requests. |
| Open-ended local speech recognition with Whisper Base | Intel N100 or equivalent processor | Home Assistant recommends at least this level for Whisper. It is a starting point, not a guarantee of identical performance across all computers, languages, or configurations. |
| Larger Whisper models or languages that need more training data | More powerful hardware than the N100 starting point | Home Assistant does not publish one universal CPU, GPU, or memory target for these cases. |
| Hands-free use from a particular room | Add a voice satellite with microphone and speaker capability | The satellite is the room endpoint; the host still runs Home Assistant and the speech pipeline. |
Speech-to-Phrase or Whisper?
Speech-to-Phrase: fast for a defined set of commands
Speech-to-Phrase is the practical choice when the assistant mainly needs to control supported devices with known phrases. Home Assistant says it runs in under one second on Home Assistant Green or Raspberry Pi 4. The trade-off is its closed set of supported commands: it does not transcribe arbitrary speech in the way an open-ended recognizer does. For example, Home Assistant’s documentation says it does not support open-ended entries such as adding an arbitrary item to a shopping list out of the box.
Whisper: broader recognition, greater host demand
Whisper is the better fit when you want to speak more freely rather than stay within a defined command set. Home Assistant recommends an Intel N100 or equivalent at minimum for Whisper Base. Its published figures illustrate why a Pi 4 may feel slower for this choice: Home Assistant reports around eight seconds to process a command on Raspberry Pi 4, versus under one second on an Intel NUC. These are Home Assistant’s indicative figures, not results from a fully specified controlled benchmark; model build, configuration, audio conditions, and processor details are not fully stated.
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Do not treat the N100 recommendation as a promise that every N100 mini PC will deliver the same speed or quality. Larger Whisper models and languages with less available training data may require more powerful hardware, and Home Assistant does not give a universal specification for those combinations.
What Raspberry Pi 4 can and cannot do
A Raspberry Pi 4 is a credible option when you use Speech-to-Phrase for supported home-control commands and Piper for spoken responses. Home Assistant describes Speech-to-Phrase as completing transcription in under one second on Pi 4. If you instead use Whisper, Home Assistant reports around eight seconds to process a command on that board, so the trade-off is slower interaction rather than an inability to run the pipeline.
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Piper is comparatively modest in this setup. Home Assistant says that on a Raspberry Pi, medium-quality Piper models generate 1.6 seconds of voice per second. That is a Home Assistant-reported rate, not a guarantee for every voice or configuration; check whether the target language and available voice quality suit your needs.
A complete Pi build also needs suitable storage, power, and the audio endpoint hardware for your chosen room setup. The documentation figures do not specify accessory models or a complete parts list, so choose those components for the particular installation rather than assuming the board alone provides hands-free audio.
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The host computer and the room satellite are different devices
The host runs Home Assistant, speech-to-text, intent handling, and text-to-speech. A satellite supplies the microphone and speaker experience in a room and may handle wake-word functions. You can use a dedicated endpoint such as Home Assistant Voice Preview Edition or a DIY microphone-and-speaker arrangement, but the satellite is not a substitute for the host computer.
Endpoint selection matters independently of host performance: microphone pickup, echo handling, placement, connection type, and compatibility affect the experience. The cited Home Assistant material establishes the endpoint’s role but does not validate or recommend specific third-party microphone or speaker models. Home Assistant also says five satellites can stream audio simultaneously without overwhelming a Raspberry Pi 4; this is its stated capacity observation, not a guarantee for every audio configuration.
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What “offline” means in this setup
A fully local voice pipeline keeps the relevant audio processing at home: microphone capture, local speech-to-text, Home Assistant intent handling, and local text-to-speech. Home Assistant describes this as spoken commands never leaving the home when the pipeline is configured locally. That does not make every Home Assistant feature or integration offline: a cloud language model, cloud speech service, weather service, or other internet-dependent integration can still send requests outside the local pipeline. Check each component you enable if keeping all voice processing local is a requirement.
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- Choose Home Assistant Green or Raspberry Pi 4 with Speech-to-Phrase and Piper if fast response to supported home-control commands matters more than flexible dictation.
- Choose an Intel N100-class host as a starting point for Whisper Base if you want open-ended local speech recognition.
- Plan for a stronger host if you need larger Whisper models or a language that performs poorly with smaller models; no universal higher-tier specification is established.
- Add a satellite for each hands-free room experience you want; select its audio hardware separately from the host.
In every case, language and task scope matter as much as nominal model support: a listed language is not evidence that recognition will be accurate enough for your household, and a fast closed-set system is not a substitute for open-ended transcription.
Quick Recap
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