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Fix a mishearing open-source smart speaker by isolating the stage that fails: wake-word detection, microphone capture, speech-to-text, or intent handling. A speaker that never enters listening mode needs a wake-word check; one that activates but records muffled audio needs an input or placement check; a wrong transcript points to capture or speech-to-text; a correct transcript followed by the wrong action points to intents, exposed entities, or supported phrasing.
Work through those stages in that order. This prevents you from retraining a wake-word model when the real problem is a selected laptop microphone, or replacing hardware when the transcript is correct and only the automation is misconfigured.
Map the symptom to the failing stage
Voice assistants are pipelines rather than single recognition engines. Rhasspy documentation separates audio input, wake-word detection, speech-to-text, and intent recognition; Home Assistant can then send the response to text-to-speech. Test each boundary independently.
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| What you observe | Most likely stage | First useful test |
|---|---|---|
| No listening indicator, wake event, or recording | Wake-word enablement, model, or microphone input | Confirm the device control has Use wake word enabled, then watch for a wake event while speaking near the microphone. |
| It activates, but the recording is silent, distant, clipped, or noisy | Microphone selection, audio route, placement, or capture processing | Make a short recording with the assistant or operating system and play it back. |
| The recording sounds clear, but words in the transcript are wrong | Speech-to-text service or its input configuration | Compare the spoken sentence with the transcript. In Rhasspy, inspect the event’s text property. |
| The transcript is accurate, but the wrong device or automation runs | Intent rules, exposed entities, or supported vocabulary | Inspect the recognized intent and the entity/action it selected; do not change the microphone first. |
Do not expect a single accuracy percentage to identify the fault. Official troubleshooting material does not establish a comparable misrecognition rate for open-source smart speakers, and older qualitative wake-word tables are not current performance benchmarks.
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Run a safe initial check
- Record the symptom. Note whether the device failed to wake, woke and stopped, produced a bad transcript, or performed the wrong action. Capture the exact phrase and the expected result.
- Restart the relevant services once. Mycroft guidance recommends restarting services as an initial check. This can clear a stuck audio process, but it is not evidence that the underlying issue is fixed. Preserve useful logs and configuration before making further changes.
- Repeat the same phrase under controlled conditions. Stand at a known distance, lower competing audio, and use the same wording. Changing several variables at once makes the result impossible to interpret.
- Follow the pipeline. Check wake-word activation, then the microphone recording, then the transcript, and finally the intent or automation. Stop changing earlier stages after they pass.
When the speaker never hears its wake word
Confirm wake-word mode is enabled
Open the device controls in your voice-assistant installation and verify that Use wake word is enabled. Home Assistant’s ATOM Echo tutorial makes this check before changing a model. A disabled wake-word option can look exactly like a dead microphone because no listening session starts.
Watch for an actual wake event
Use the device’s listening indicator, event stream, or log while saying the configured wake phrase. If there is no event, the failure is before speech-to-text. If an event appears but no usable recording follows, move to the microphone test rather than retraining the wake word.
Adjust or recreate the wake-word model
If the microphone records your voice clearly but the wake phrase is missed, try the configured wake-word model. Home Assistant’s ATOM Echo procedure includes adjusting the model and creating a new model when necessary. Change one model setting at a time and test several repetitions from the position where the speaker normally sits.
Keep the test fair: use the exact wake phrase, normal speaking volume, and both quiet and typical room conditions. A model that works only when you shout close to the capsule is not a practical fix.
Test another satellite when available
Try the same phrase on a second compatible speaker or satellite. If one unit wakes and another does not, the problem is probably local to the failing unit’s microphone, placement, firmware, or model configuration. If every unit fails, inspect the shared wake-word service or configuration.
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Separate wake-word and microphone problems
Mycroft’s wake-word guidance recommends checking whether the microphone is the underlying problem before blaming the model. A wake-word detector cannot respond reliably to audio that is silent, clipped, routed from the wrong input, or overwhelmed by noise. Perform the record-and-playback check below before spending time on model changes.
When it wakes but captures poor audio
Make a record-and-playback test
- Open the assistant’s audio capture test or the operating system’s recording utility.
- Select the microphone that is physically installed in the speaker or satellite. Do not assume the default input is correct, especially when USB, Bluetooth, webcam, and onboard inputs are all present.
- Record a short sentence from the normal speaking position. Include a wake phrase followed by a simple command such as Turn on the lights in the kitchen.
- Play the file through headphones or another speaker. Check whether speech is intelligible, whether the beginning or end is clipped, and whether background audio dominates.
- Repeat with the assistant’s capture path, if it provides one. A clear operating-system recording but a bad assistant recording indicates an input-selection, format, service, or routing problem.
Mycroft’s audio troubleshooting material uses this record-and-playback approach, and Rhasspy exposes device discovery and audio-input services for verifying the route. The exact menu names vary by installation, so record the device name and input selected in your own system.
Correct the physical setup
- Move the satellite so its microphones face the room rather than a wall, enclosure, or furniture edge.
- Keep it away from a television, fan, air conditioner, or speaker that masks speech.
- Do not cover microphone openings with a case, cloth, dust, or decorative material.
- Check that a cable or connector is fully seated and that the device receives stable power.
- Test at the distance and angle used in daily life, not only with your mouth directly over the microphone.
These changes address capture quality; they do not repair an incorrect intent rule. Once playback is clear, move forward to the transcript stage.
Consider a multi-microphone speakerphone only after proof of a capture problem
Home Assistant’s wake-word overview notes that speakerphones with multiple microphones and audio-processing chips can capture voice cleanly. Treat this as an audio-capture category, not a universal cure. Confirm the operating-system connection, input format, wake-word support, and assistant compatibility before buying or wiring one. The available documentation does not establish that a particular USB speakerphone works with every voice satellite.
When the transcript contains the wrong words
Inspect the text received by the assistant
Do not use wake-word retraining to solve a command transcription error. Rhasspy documents the recognized sentence in the text property and the initiating wake word in wakewordId. Compare those fields with what you actually said. This establishes whether the command reached speech-to-text and what text the intent layer received.
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Retest with cleaner input
- Move closer to the microphone without speaking directly into it.
- Pause briefly after the wake indication so the first word is not clipped.
- Lower music, television, fans, and other voices.
- Use a short, unambiguous sentence, then repeat the original wording.
- Compare the new recording and transcript with the first attempt.
If the recording itself is poor, return to microphone selection and placement. If recordings are clear but the words remain wrong, inspect the configured speech-to-text service and its input settings. A local speech-to-text engine and a remote engine can behave differently, and changing between them changes the diagnostic path; verify which one your installation actually uses.
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Confirm that the speech-to-text service is configured for the language and audio format you are speaking. Check that the service is reachable and that the assistant is sending it the intended microphone stream. Avoid changing wake-word models, microphone hardware, and speech-to-text engines simultaneously; isolate one variable and repeat the same phrase.
When the transcript is right but the action is wrong
Inspect intent recognition separately
A correct transcript proves that the microphone and speech-to-text stages may be functioning. Rhasspy treats intent recognition as its own service stage. Inspect the recognized intent, slots, entities, and target action rather than replacing the microphone.
Verify entities are exposed
In Home Assistant, confirm that the device, light, scene, or other entity is exposed to the conversation system. An entity that exists in the dashboard but is not exposed cannot be selected by a voice intent. Check names, areas, aliases, and whether the entity is currently available.
Use supported phrasing and vocabulary
Compare the transcript with the phrases your configured assistant accepts. A sentence can be transcribed perfectly yet fail because it does not match an intent pattern, uses an unsupported synonym, or leaves the target ambiguous. Test a documented, simple form first, then add aliases or patterns deliberately.
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Trace the selected target and action
When the wrong light, room, or scene runs, inspect how the intent mapped words to entities. Look for duplicate names, stale aliases, broad patterns, and defaults that apply when a slot is missing. Correct the rule or exposure, then rerun the unchanged spoken phrase to verify that only the downstream behavior changed.
Use events and logs to prove where it fails
Logs are most useful when you know what evidence each stage should produce. Keep a timestamped note for one test phrase and look for the following sequence:
- Wake event: the satellite reports that the configured wake word was detected. In Rhasspy-related events, the initiating word is represented by
wakewordId. - Audio session: the assistant starts and ends capture. Missing or extremely short audio points to the microphone route or timing.
- Transcript: text is returned. Rhasspy exposes it as
text. An absent value indicates a speech-to-text or transport problem; an incorrect value indicates capture or transcription quality. - Intent: the text is classified and entities or slots are selected. A correct transcript with a wrong intent keeps the investigation downstream.
- Action and response: the selected service runs and text-to-speech responds. Failure here can be an automation, permissions, availability, or output-audio issue rather than a hearing problem.
Save the relevant log lines before changing configuration. A restart can erase the context needed to distinguish a transient service failure from a repeatable recognition problem.
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M5Stack ATOM Echo as a documented example
Home Assistant’s wake-word tutorial uses the M5Stack ATOM Echo as a small voice-assistant satellite and provides device-specific checks for enabling wake words and adjusting or recreating a model. It is a useful example for someone testing a compatible satellite or replacing that exact unit. It is not evidence that the same procedure or hardware solves every open-source speaker’s mishearing.
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The speaker model, connector, board revision, and wiring determine whether a replacement part is compatible. Without those details, naming a supposedly matching microphone, cable, or board would be unsafe. First prove that the existing capture path is faulty, then use the device’s service documentation or a part number specific to that model.
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Compare alternatives on the right axes
If you decide to use another satellite, compare microphone pickup and audio-processing hardware, compatibility with the chosen assistant and operating system, whether wake-word detection runs on the device or server, whether speech-to-text is local or remote, and the setup and maintenance burden. Available documentation does not provide a controlled head-to-head test, so it cannot support a claim that one option is objectively more accurate.
Understand the local and offline privacy path
Home Assistant documents a fully local voice path: the microphone hears speech, local speech-to-text converts it to text, Home Assistant interprets the request, and local text-to-speech speaks the response. Its Rhasspy integration describes Rhasspy as open source and fully offline. Those are supported configuration options, not a guarantee about every installation.
Check the actual speech-to-text and text-to-speech services configured on your system. A pipeline can use local wake-word detection while sending transcription to a remote service, or combine local and remote components. Record which services handle each stage before evaluating privacy, latency, or network failures.
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| Test | Pass condition | If it fails |
|---|---|---|
| Wake-word toggle and event | The configured option is enabled and a wake event appears. | Correct the device setting, model, or shared wake-word service. |
| Raw recording | Playback contains clear speech from the intended microphone. | Fix input selection, routing, placement, noise, power, or hardware. |
| Transcript | The returned text matches the spoken command. | Retest closer and quieter; then inspect speech-to-text configuration. |
| Intent and entities | The expected intent selects the exposed target. | Correct vocabulary, aliases, entity exposure, slots, or rules. |
| Action and response | The selected service runs and the response is audible. | Inspect automation permissions, target availability, and output audio. |
Write down the result of each row. Once a row passes repeatedly, leave it alone while investigating the next row. This is faster and safer than repeatedly changing the entire voice stack.
Common mistakes that waste time
- Retraining before recording: a wake-word model cannot compensate for a muted or wrong microphone.
- Changing several services at once: you lose the comparison that identifies the failing stage.
- Assuming the default input is correct: operating systems often switch to a webcam, headset, or USB device.
- Calling a correct transcript a recognition failure: if the words are right, inspect intents and exposed entities.
- Treating a restart as a repair: a restart is a quick check, not proof of a durable fix.
- Buying hardware without compatibility details: connector, operating system, assistant integration, and wake-word support all matter.
- Assuming local branding means local processing: verify every speech-to-text and text-to-speech service in the configured pipeline.
When to stop troubleshooting and escalate
Escalate to device-specific documentation or community support when the microphone recording remains silent or electrically noisy after selecting the correct input and checking power, when a known-good microphone fails on the same host, or when logs show a repeatable service error that the configuration controls cannot resolve. Include the exact speaker model, operating system, assistant version, selected input name, one timestamped test phrase, the recording result, the transcript, and the intent result. Do not publish private audio or credentials in a support post.
For older Mycroft material or the older Rhasspy wake-word guide, verify current interface labels and hardware requirements against your installed versions. Home Assistant documentation reviewed on October 11, 2026 is current at that date, but device support and labels can change.
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