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Stt — DSH Plugin for DeepSeek Harness
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@try-works/dsh-stt

Stt

Multi-model local speech-to-text for the DSH Web composer: Whistle and Voz, user-selectable, with lazy per-model download. Ships as a DSH bundle.

The plugin will be installed here. Keep web if you are unsure.

npx -y @deepseek-ai/dsh plugin --profile web add github:try-works/dsh-stt#8ea07c6cb1efb7f6aa46f4b16b9bac66ba8514f6
READMECompatibilityVersions
Plugin screenshot

Compatibility and provenance

Stt is published as @try-works/dsh-stt and currently resolves to version 0.2.6. The Hub verifies its manifest and preserves the exact installation source for reproducible installs.

DSH compatibility
*
Runtime surfaces
web
Release source
github
Registry updated
10/16/2026

Versions

0.2.6stable
10/8/2026
0.2.5stable
10/8/2026
0.2.4stable
10/8/2026
Show 5 more versionsCollapse versions
0.2.3stable
10/7/2026
0.2.2stable
10/7/2026
0.2.1stable
10/7/2026
0.2.0stable
10/7/2026
0.1.4stable
10/7/2026

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Latest
0.2.6
DSH
*
HMR
Process restart
Tree shaking
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Unpacked size
Unavailable
Files
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Surface
web
License
MIT
Source
github
GitHub
★ 2
Weekly downloads
2,107
Last push
10/8/2026
View source ↗Project homepage ↗
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README

dsh-stt

Multi-model local speech recognition for the DeepSeek Harness Web composer.

Source and issues: github.com/try-works/dsh-stt.

A microphone appears between the model selector and Send. Click once and start talking — the recording ends on its own about a second after you stop speaking, and the transcript is inserted into the draft for review. You choose which on-device model transcribes, and nothing is downloaded until you choose it.

The recognizer is loaded when you start recording, not when you finish, so the wait happens behind your own voice instead of after it.

Models

PickSizeLanguagesNotes
Whistle (Cactus Compute)18.4 MB7, auto-detecteddefault; loads in 30 ms, ~116 MB RAM
Voz (Desert Ant Labs)~390 MB25higher accuracy; ~1 GB RAM while warm
SenseVoice——coming soon — advertised only, downloads nothing

Both working models were measured end-to-end on Windows and each transcribed a 7.62 s clip correctly: Whistle in 1.52 s using 116 MB, Voz in 2.39 s.

Install

This is a rider on the shipped voice bundle: that bundle supplies the microphone UI and the speech service, and this package adds the models. Install both, in this order — layers apply in list order and a later layer wins for a given row id:

# The voice-bundle version MATTERS: plain `add` resolves the npm `latest` tag
# (0.1.7-alpha.1), which does not match a DSH 0.2.0-rc.2 runtime. Pin yours.
dsh plugin --profile web add @deepseek-ai/dsh-experimental-voice-input-bundle@0.2.0-rc.2
dsh plugin --profile web add @try-works/dsh-stt

Installing from a checkout instead of the registry works the same way: dsh plugin --profile web add /path/to/dsh-stt.

Then open Settings → Plugins → Voice Input and pick a model. The picker lists every model with its size and time estimate; Download and prepare fetches only the one you selected.

Configuration

cordis.patch.yml carries the whole configuration. Each model is a key under providers:

providers:
  whistle-local:
    enabled: true
  voz-local:
    enabled: false        # keep 390 MB out of the picker entirely
  sensevoice-local:
    enabled: true         # placeholder only
FieldMeaning
enabledfalse stops the provider registering — it is never listed, selected or downloaded
modelRootwhere that model's files live; defaults to <dataRoot>/<key>
idoverride the provider id (advanced; the selection is stored by id)
nameoverride the display name shown in the picker

dataRoot is required and must be an absolute path.

How the recording ends

A silence gate watches the microphone level. Nothing stops until it has heard 300 ms of speech, so a cough or a door cannot end a recording before you have said anything; after that, 1.2 s of quiet ends it. The Stop button is still there, and Escape or switching away cancels and discards.

Because this needs the microphone level, the plugin ships its own browser half and registers it into the composer slot at a lower priority than the shipped microphone, which therefore stops rendering. That is also why the wait disappears: the same half asks the host to load the model the moment recording starts.

Architecture

src/index.js              register every enabled provider
src/config.js             schemastery configuration
src/provider-kit/
  http.js                 resumable download (see below)
  preparation.js          disk inspection + the state the UI renders
  oneshot.js              one process per recording
  worker.js               one warm process, idle-reclaimed
src/providers/whistle/    one-shot: needle.exe per recording
src/providers/voz/        warm worker holding the model
src/providers/sensevoice/ placeholder: advertises, never downloads

Two deliberate engine strategies

Whistle runs one process per recording. Its engine loads the 16.9 MB model in ~30 ms, so paying that per request buys real crash isolation and automatic memory reclamation. It also satisfies the engine's one process-global model per kind rule for free.

Voz runs as a warm worker because its load costs 6.2 s and about a gigabyte; the child persists between recordings and is released after five idle minutes.

Why we download the models ourselves

Voz.load() fetches its 384,832,967 bytes with a single fetch per file and no retry, no resume and no timeout. On a real connection that failed at 37.5% of the largest file, and a resumable retry hit three more drops. Preparation therefore pre-populates Voz's cache with a resumable Range download, after which Voz.load({ cache: true }) adopts the files without fetching.

Limitations

  • Insert, not send. The transcript lands in the draft; you press Enter. No message is ever sent on your behalf.
  • The microphone UI is the shipped one. This package contributes providers only, because the picker is keyed to the shipped voice bundle's detail page.
  • SenseVoice is advertised, not delivered. Its entry cannot be downloaded; see the hand-over note in src/providers/sensevoice/index.js.
  • Recording limits are the seam's defaults: 4 MB and 120 s per recording. Whistle's engine accepts only 30 s per call, so a longer recording is cut at the quietest nearby moment and transcribed in segments that are joined in order. Nothing to configure; 45 s of speech costs roughly 12 s of inference.
  • Local means the Host machine, which may be remote from your browser.