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Yes, you can add spoken commands or NPC conversation without uploading microphone audio—but only if every audio-processing stage you use is local. The usual design is microphone capture, local speech-to-text (STT), text sent to game logic, and optional local response generation and text-to-speech (TTS). A local Whisper recognizer protects the recognition step; it does not automatically make an LLM, TTS service, telemetry system, voice-chat service, model download, or crash reporter offline.
The safest implementation starts with deliberate recording controls, runs an on-device STT model, validates the resulting text before it can trigger gameplay, and audits all network traffic separately. The sections below show how to choose an implementation, configure capture, handle Windows and Unity-specific constraints, and verify that audio and transcripts stay on the player’s machine.
What a fully local in-game voice pipeline looks like
A privacy-preserving voice feature has several independent stages. Treat each stage as a separate trust boundary rather than calling the whole feature “offline” because one model runs locally.
- Microphone capture: the game requests operating-system permission and records only after a visible, deliberate action such as push-to-talk.
- Recording boundary: the game stops on button release, a maximum-duration limit, or voice-activity detection (VAD) that recognizes silence.
- Local STT: an on-device runtime converts the audio waveform into text. Whisper models are one option.
- Game routing: recognized text enters the existing command, dialogue, or mod-event system. It should be validated before performing consequential actions.
- Optional response generation: a rules engine, local language model, or remote service generates a reply. This choice determines whether conversation text leaves the device.
- Optional TTS: a local synthesizer speaks the reply. Cloud TTS creates a separate network boundary.
If you require that no captured speech leave the computer, confirm the behavior of every component, including first-run model downloads, updates, telemetry, logs, online LLM calls, cloud TTS, voice chat, and crash reporting. “Local STT” is a precise claim about recognition, not proof that the game is entirely disconnected.
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Choose the implementation route
Your engine, target operating system, distribution channel, and acceptable maintenance burden matter as much as model accuracy. These routes are documented examples, not interchangeable benchmarks.
| Route | What it provides | Important checks before shipping |
|---|---|---|
| SkyrimNet local Whisper | A game/mod-specific offline recognizer. Its documentation says audio is processed on-device and the resulting text can drive actions, dialogue, or mod behavior. It offers several English Whisper models and a Skyrim-focused fine-tune. | Confirm compatibility with the exact game and mod versions, NVIDIA CUDA support, model storage and download behavior, and accuracy for the player’s language and vocabulary. Its hardware guidance applies to this implementation only. |
| Unity components documented by PlayKit | A microphone recorder, built-in VAD, and a separate transcription client. The example uses a 16 kHz sample rate recommended for Whisper and exposes a maximum recording duration. | The documentation does not, by itself, establish that the transcription client is local. Verify the selected configuration, licensing, platform support, permission UX, and network behavior. The microphone recorder is not supported on WebGL. |
| Windows Speech Recognition API | Batch and streaming on-device transcription. Microsoft documents NPU use on Copilot+ PCs and CPU use on other supported devices; GPU is not supported. | The cited API is experimental. It requires Windows 11 version 24H2 or later, an experimental Windows App SDK release, and supported CPU/NPU hardware. Check model readiness, consent for downloads, and whether your distribution channel can depend on an experimental API. |
| Custom Whisper with Windows ML | You provide Whisper encoder and decoder ONNX files plus a tokenizer. The API supplies streaming output and cancellation. | Microsoft marks the runtime and Speech Recognition APIs experimental and unsupported for production in the cited documentation. Plan model packaging, execution targets, language support, and integration language carefully; the cited documentation does not support C#. |
When two options appear viable, compare target OS and engine support, verifiable local processing, API maturity, language and vocabulary coverage, measured latency on the target machine, CPU/GPU/NPU load while the game runs, model size and first-run download, update burden, and microphone controls.
Plan the feature before choosing a model
Fixed commands need less than open conversation
Decide whether speech will trigger a small set of commands (“open map,” “equip torch”), select dialogue options, provide free-form NPC conversation, or carry voice chat. A narrow command grammar can reject unknown phrases and may work acceptably with a smaller model. A general-purpose LLM is not required merely because the input is spoken. Free-form conversation needs additional intent handling, safety checks, and usually a response generator.
Define the privacy promise precisely
Write down what “local” means for your build. Possible promises include “microphone audio is never uploaded,” “audio and transcripts are never uploaded,” or “the game can run without a network connection after models are installed.” These are different promises. Model downloads, automatic updates, analytics, online accounts, crash reports, and multiplayer voice services can still use a network even when STT is local.
List the supported platforms
Record the engine, operating-system versions, CPU/GPU/NPU classes, and storefront or launcher constraints. A path that works on a Windows desktop may not work in a browser build: PlayKit explicitly says its microphone recorder is not supported on WebGL. Treat console, handheld, macOS, and Linux support as separate engineering targets unless your chosen runtime documents them.
Build the pipeline step by step
1. Request permission and make recording obvious
Operating systems require microphone permission. Explain why the game needs it, show the current state with an icon or label, and provide a stop or cancel action. A push-to-talk key is easier to reason about than an always-listening microphone. If you offer a wake word or automatic activation, tell the player when buffering starts and how to disable it.
- Show an unambiguous idle, recording, processing, and error state.
- Never begin capture merely because the game loaded.
- Keep the stop control available if focus changes or the recognizer stalls.
- Explain whether temporary audio is held in memory, written to disk, or deleted after transcription.
2. Capture audio with a bounded duration
Choose a sample rate and channel layout accepted by the recognizer. PlayKit’s Unity example uses 16 kHz as the recommended rate for Whisper and exposes a configurable maximum recording duration. A fixed upper bound prevents an accidental open microphone from consuming memory or delaying transcription.
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For push-to-talk, begin recording on press and stop on release or the maximum duration. For hands-free input, VAD can detect silence and end the utterance; it should include a short trailing-silence window so the final word is not clipped. Test VAD against game music, explosions, fans, and voice chat rather than assuming a quiet-room threshold will work.
3. Run speech-to-text on the device
Package the model and runtime, or download them with explicit consent during setup. Keep the model files in a location that the game can read without uploading audio. If a runtime downloads a model on demand, disclose the download size, destination, and network requirement before the first use.
Whisper model size is a quality and resource trade-off. SkyrimNet documents these English choices:
| Model file | Documented characteristic | Practical implication |
|---|---|---|
ggml-base.en.bin |
Lightweight and fast; English only. | Useful when responsiveness and a small footprint matter more than maximum recognition accuracy. |
ggml-medium.en.bin |
Higher accuracy with moderate performance. | A middle option when the machine can spare more compute during gameplay. |
ggml-large.en.bin |
Highest accuracy in the listed set but slower. | Requires more headroom and should be tested while the game is rendering. |
ggml-large.en-skyrim.bin |
A large fine-tune for Skyrim terminology. | Potentially better for that game’s names and vocabulary; it is not a general recommendation for other games. |
SkyrimNet’s documented real-time route is GPU-accelerated, requires NVIDIA CUDA, does not support CPU use in production, and recommends an NVIDIA GTX 1060 or better with at least 6 GB of VRAM. Those are SkyrimNet implementation requirements, not universal Whisper requirements. Other runtimes may use a CPU, GPU, or NPU with different model formats and limits.
4. Route the transcript as untrusted input
Send the recognized text to a command parser, dialogue system, or mod event rather than executing arbitrary text. For fixed commands, normalize case and punctuation, match against an allowlist, and show a confirmation for destructive or irreversible actions. For free-form dialogue, pass the text to the conversation system with a clear timeout and cancellation path.
A safe engine-agnostic flow is:
onPushToTalkPressed() -> startCapture() -> showRecordingState()
onPushToTalkReleased() -> stopCapture() -> localTranscribe(audio)
transcriptReady(text) -> validateIntent(text)
validCommand(intent) -> executeGameAction(intent)
invalidOrUnclear(text) -> askForRepeatOrShowChoices()The function names above are illustrative; use the interfaces supplied by your engine and runtime. Do not treat a transcript as authenticated player intent: background speech, another player’s voice, or a recognition error can produce valid-looking words.
5. Keep response generation local when required
If an NPC reply must also remain offline, use authored dialogue, a local rules system, or a local language model and verify that its model and runtime do not call a hosted endpoint. A local STT result sent to a cloud LLM is still a cloud voice pipeline from the player’s privacy perspective because the transcript contains the spoken content.
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6. Add local TTS only if needed
Text-to-speech is independent of STT. Choose a local synthesizer if spoken replies must remain offline, and document where voice models are stored. If the game uses a hosted TTS service, say explicitly that generated text or audio leaves the device even though recognition was local.
Using SkyrimNet’s documented local Whisper feature
SkyrimNet describes “Local Whisper STT” as an offline speech-recognition system powered by the open-source Whisper model. The documented feature processes audio on-device and can pass transcribed text to actions, dialogue, or mod behavior.
- Check that the installed Skyrim and SkyrimNet versions are compatible.
- Verify an NVIDIA GPU with CUDA support. SkyrimNet recommends a GTX 1060 or better and 6 GB or more of VRAM for its documented real-time path.
- Choose an English model based on the speed-versus-accuracy trade-off and Skyrim vocabulary needs.
- Confirm where the model is downloaded or stored and whether setup requires network access.
- Enable microphone permission and configure the feature’s activation control.
- Test recognition with the game’s music, combat sounds, accents, names, and mod terminology.
- Inspect other SkyrimNet and game features separately for online LLM, telemetry, update, or crash-reporting connections.
Calling this feature offline is accurate for its documented recognition component. It is not evidence that every service in a modded game session is offline.
Integrating a Unity game
PlayKit’s Unity documentation separates microphone recording, VAD, and a transcription client. Its example recommends a 16 kHz sample rate for Whisper and allows a maximum recording duration. Use those details to design the capture layer, then verify the transcription client’s processing location before promising no cloud transmission.
Recommended Unity integration sequence
- Request microphone permission through the platform’s permission system and display the result.
- Configure the recorder’s sample rate and maximum duration; use 16 kHz when it matches the selected Whisper runtime.
- Choose push-to-talk or VAD and expose a cancel action.
- Convert the completed clip into the format required by the local STT runtime.
- Start transcription asynchronously so rendering remains responsive.
- Handle partial results only as provisional text; execute commands after a final result and validation.
- Disable or replace the recorder for WebGL, which the documentation lists as unsupported.
Do not infer local processing from the presence of a “transcription client.” Inspect its endpoint configuration, package documentation, and runtime network requests. A Unity recorder can be local while a separate transcription service is remote.
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Windows on-device options and their limits
Windows Speech Recognition API
Microsoft documents batch and streaming on-device transcription. The cited prerequisites are Windows 11 version 24H2 or later, an experimental Windows App SDK release, and supported CPU or NPU hardware. Copilot+ PCs can use an NPU; other supported devices can use a CPU. GPU execution is not supported by this API.
Microsoft recommends, for a good CPU experience with this specific API, at least four physical cores, a 3 GHz base clock, and 32 MB of L3 cache. These are recommendations, not universal local-STT minimums. Latency and real-time quality vary with CPU performance and the game’s concurrent workload.
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On CPU-only devices, Microsoft says the model may be downloaded on demand through Windows Update and recommends asking the user’s consent before a background download. Make that consent part of setup, not a hidden first microphone press. Microsoft currently labels the relevant API experimental, so assess the risk of breaking changes before shipping it as a production dependency.
Custom Whisper with Windows ML
The documented custom route requires you to supply Whisper encoder and decoder ONNX files and a tokenizer. The API handles streaming output and cancellation, while you control model packaging and execution targets. Microsoft likewise labels the Windows ML runtime and Speech Recognition APIs experimental and unsupported for production in the cited documentation, and the cited material does not support C#.
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Scan for outdated or missing drivers - takes under a minuteDriver Scan →Clear out junk files and repair common Windows errorsFree Scan →This route can make model choice and distribution more explicit, but it increases your responsibility for ONNX files, tokenizer compatibility, language coverage, hardware acceleration, updates, and installation size. Test cancellation and partial-result handling under load before connecting output to gameplay.
Measure performance on the machine that will run the game
No universal speed or accuracy figure can be applied across Whisper runtimes, models, engines, and hardware. Measure your own build under realistic conditions.
- End-to-end latency: time from the end of speech to a usable final transcript, not just model inference time.
- Recognition quality: test accents, quiet and noisy rooms, character names, invented terms, and speech over game audio.
- Resource use: record CPU, GPU or NPU utilization, VRAM, system memory, temperature, and frame-time impact while the game is active.
- Streaming behavior: verify that partial text is visibly marked as provisional and that cancellation stops both inference and gameplay actions.
- Failure handling: unplug the microphone, deny permission, fill storage, interrupt a model download, and cut network access after installation.
- Repeatability: run the same utterance set across model sizes and hardware classes; do not present one machine’s result as a general benchmark.
Large models may improve difficult-word recognition while increasing delay and contention with rendering. Smaller models can feel better for short commands even when their transcripts need more confirmation. Select based on the feature’s tolerance for errors, not on model size alone.
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Before release, document the complete path from microphone to disk and network. A local model does not replace transparent controls.
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- Capture: when does recording begin, and is any pre-roll buffer retained?
- Storage: is raw audio held only in memory, cached temporarily, or written to a file? How is it deleted?
- Transcripts: are final or partial transcripts logged, synced, or included in crash reports?
- Models: where are model files stored, and do setup or updates contact a server?
- Other AI: do LLM, moderation, translation, or TTS components send text or audio off-device?
- Telemetry: does analytics record activation counts, utterance length, recognized text, or error payloads?
- Multiplayer: is a separate voice-chat service active even when the game’s command recognizer is local?
- Controls: can the player revoke microphone permission, clear logs, delete downloaded models, and disable voice features?
Use operating-system permission prompts, an in-game privacy explanation, and a visible recording indicator. If the game cannot function without a first-run model download, state that requirement and its network destination in plain language.
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Troubleshooting common failures
The microphone is unavailable
Check operating-system permission, the selected input device, exclusive-mode settings, and whether another application owns the microphone. Confirm that the game displays a permission-denied state instead of silently retrying.
Transcription is delayed or causes stutter
Reduce maximum clip length, use VAD or push-to-talk, select a smaller model, move inference to the supported accelerator, and profile frame time while the game renders. Do not assume a GPU path exists: Microsoft’s Windows Speech Recognition API does not support GPU execution, while SkyrimNet’s documented real-time path specifically requires NVIDIA CUDA.
Words are cut off
Increase the VAD trailing-silence window, release push-to-talk slightly later, and inspect resampling and channel conversion. Keep the final transcript separate from partial output so a prematurely ended phrase cannot trigger an action.
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Inspect model setup, update checks, telemetry, crash reporting, LLM and TTS endpoints, and multiplayer services independently. Disable network access after installation as a controlled test, then review which feature fails. A successful local transcription does not prove that the rest of the pipeline is disconnected.
Recognition is poor for names or commands
Use a model or vocabulary appropriate to the game, constrain command parsing, improve microphone placement, and test with game audio enabled. SkyrimNet documents a Skyrim-tuned large model; that specialization should not be assumed to transfer to another title.
When local voice AI is the right choice
Local processing is most compelling when microphone privacy, offline play, predictable recurring costs, or low dependence on a service provider matters more than minimum installation size. It also gives the game control over model versions and failure behavior. The trade-offs are local CPU/GPU/NPU load, storage for models, first-run setup, platform-specific integration, and your responsibility for updates and accuracy.
For a small command vocabulary, a local recognizer plus an allowlisted parser is usually easier to secure than a free-form conversational stack. For NPC conversation, decide separately whether the dialogue generator and TTS are local. For a Windows release, treat the cited Microsoft APIs as experimental; for a SkyrimNet mod, treat its CUDA and GTX 1060/6 GB guidance as implementation-specific; for Unity, verify that the transcription component—not merely the microphone recorder—is configured for local inference.
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1Fix the driver behind crashes, sound loss and screen glitches2Repair Windows errors before they cause bigger problems3Scan for outdated or missing drivers - takes under a minuteThe defensible promise is therefore specific: state exactly which component processes audio on-device, what downloads or online services remain, and how players can see and control recording. Only after that audit can you claim that a game’s voice feature runs without sending audio to the cloud.
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