lattifai/edgespeak-skills · Archived

edgespeak-broadcast

Turn text into natural speech fully on-device via EdgeSpeak (Broadcast) — synthesize WAV audio with official named voices, cloned voices, style instructions, speed and reproducible seeds, design a brand-new voice from a text description, and manage a local voice library including cloning a voice from consented reference audio.

First seen Jul 28, 2026

Installation

$ npx skills add lattifai/edgespeak-skills --skill edgespeak-broadcast

Summary

  • Turn text into natural speech fully on-device via EdgeSpeak (Broadcast) — synthesize WAV audio with official named voices, cloned voices, style instructions, speed and reproducible seeds, design a brand-new voice from a text description, and manage a local voice library including cloning a voice from consented reference audio.
  • Use when the user wants local private text-to-speech, an audio version of some text, or wants to list/add/delete EdgeSpeak voices.

Stronger alternatives

This repository is archived — consider an actively maintained alternative.

Similar popular skills

Related neighbors and high-traction skills in the same topics — useful to compare before installing.

Also in this package

Other skills from lattifai/edgespeak-skills.

npx skills add lattifai/edgespeak-skills

Browse all from lattifai/edgespeak-skills

More details

Agent compatibility

Declared targets from SKILL.md / docs. Unmarked agents are not listed — the skill may still install via the CLI.

Claude Code Not declared
Cursor Not declared
Codex Not declared
GitHub Copilot Not declared
Windsurf Not declared
Gemini CLI Not declared
Cline Not declared
OpenCode Not declared

Repository health

Stars 6
License LICENSE
Default branch main
Open issues 0
Status Archived

Skill metadata

Parsed from SKILL.md frontmatter.

Version0.2.0

Package contents

Files included with this skill beyond the listing page.

  • skill md SKILL.md 16,623 B
  • docs SUMMARY.md 488 B

History

  1. First seen on skills.sh
  2. First recorded snapshot · 6 installs

SKILL.md

EdgeSpeak Broadcast

Turn text into speech, entirely on-device — the text never leaves the machine. Broadcast is EdgeSpeak's speech feature; under the hood this skill calls edgespeak-cli speech (alias: synthesize). When the EdgeSpeak desktop app is running, the CLI talks to its local gateway (OpenAI-compatible, 127.0.0.1:1117) and reuses the warm model (proxy mode); when the app is not running, the CLI launches the bundled on-device engine itself (standalone mode). Standalone is a normal mode, not an error.

Version compatibility. The frontmatter pins this skill's version and the oldest CLI it is written against (minCliVersion). If edgespeak-cli --version reports something older, run edgespeak-cli update (or re-run the installer) before relying on the flags documented here. Same-numbered builds can still differ, so --help is the tiebreaker for flags — a flag documented here but missing from the installed --help means update, don't route around it.

--help is not the tiebreaker for model ids: speech --help names only a subset of the installed TTS models. The live, authoritative list is the gateway's /v1/models — see "Pick a model and a voice".

Inputs to confirm

  • The text to speak (or the file it comes from).
  • Output WAV path.
  • Any requested voice, style instructions, speed, language, or reproducibility (seed) preferences.
  • Whether the user wants a named voice (a specific, reusable EdgeSpeak voice identity), a cloned voice (their own user: voice), or a designed voice (invented from a text description) — the answer decides the model, not just the --voice value.

How to do it

  1. Check the runtime first:

``bash edgespeak-cli status ``

- Command not found → the CLI isn't installed. On Windows x64, tell the user to install the EdgeSpeak desktop app, which ships the CLI. On macOS Apple Silicon or Linux x8664, use curl -fsSL https://edgespeak.com/install.sh | sh (self-contained, no desktop app needed; on Linux the installer auto-detects NVIDIA GPUs and installs a CUDA-enabled runtime). - License not activated / locked → run edgespeak-cli login to sign in via the browser (purchased accounts activate this machine directly, new accounts start a free 7-day trial; signing in also replaces an anonymous trial with your account credentials), or edgespeak-cli activate <KEY> with an existing key. No account and no browser at hand? edgespeak-cli trial starts an instant anonymous 7-day trial (device-bound, one per device). Non-interactive runs (agents, pipes, CI) fail fast with licenserequired instead of prompting. - Gateway not running (standalone) → this is fine; speech will launch the bundled on-device engine itself.

  1. Pick a model and a voice together. They are not independent choices — every TTS model accepts

one family of voices and rejects the others (see "Pick a model and a voice" below).

  1. Synthesize:

```bash edgespeak-cli speech "<text>" -o out.wav [options]

# Default: the general-purpose clone-capable model with a preset voice edgespeak-cli speech "<text>" -o out.wav --voice builtin:warm-neighbor

# A specific official named voice (needs a CustomVoice model) edgespeak-cli speech "<text>" -o out.wav \ -m Qwen/Qwen3-TTS-12Hz-1.7B-CustomVoice --voice builtin:Serena

# Named voice plus a speaking style (only the 1.7B CustomVoice model honors --instructions) edgespeak-cli speech "<text>" -o out.wav \ -m Qwen/Qwen3-TTS-12Hz-1.7B-CustomVoice --voice builtin:Aiden \ --instructions "a calm news anchor, measured and clear"

# Voice design: invent a voice from a text description (no reference audio needed) edgespeak-cli speech "<text>" -o out.wav \ -m Qwen/Qwen3-TTS-1.7B-VoiceDesign --voice builtin:auto \ --instructions "a warm, calm narrator with a low voice" ```

The WAV is written to -o and a JSON result is printed to stdout. Engine logs go to stderr — when scripting, parse stdout only.

Do not silently overwrite an existing output file. speech clobbers an existing -o WAV without warning. If the requested path already exists and the user did not explicitly ask to overwrite or regenerate that exact file, confirm with the user first (or agree on a different path); if you cannot ask, write to a new non-conflicting path and say so in your answer.

Pick a model and a voice

Ask the gateway what the installed TTS models can do (the app must be running):

curl -s http://127.0.0.1:1117/v1/models \
  -H "Authorization: Bearer $EDGESPEAK_API_KEY"

Every model whose supported_endpoints include /v1/audio/speech declares a features array:

Feature Meaning
named_voice Accepts EdgeSpeak's official named voices — and only those
voice_clone Accepts the cloneable preset voices, your own user:<uuid> voices, and builtin:auto
instruct Actually honors --instructions style text
liveaudiostreaming The engine can emit audio while still synthesizing (this is what the app's Broadcast player uses to start speaking early; speech still writes one finished WAV, so it changes nothing for this skill)

Those features resolve to six local models. Pass the id verbatim:

Model id Voices it accepts instruct Streaming
k2-fsa/OmniVoice (CLI default) presets, user: clones, builtin:auto no no
Qwen/Qwen3-TTS-0.6B-Base presets, user: clones, builtin:auto no yes
Qwen/Qwen3-TTS-12Hz-1.7B-Base presets, user: clones, builtin:auto no yes
Qwen/Qwen3-TTS-12Hz-0.6B-CustomVoice official named voices only no yes
Qwen/Qwen3-TTS-12Hz-1.7B-CustomVoice official named voices only yes yes
Qwen/Qwen3-TTS-1.7B-VoiceDesign builtin:auto only yes (required) no

Three of them also answer to a short alias: k2-fsa/OmniVoice → omnivoice, Qwen/Qwen3-TTS-0.6B-Base → qwen3-tts-0.6b-base, Qwen/Qwen3-TTS-1.7B-VoiceDesign → qwen3-tts-1.7b-voice-design. The three 12Hz models have no short alias — a guessed one (qwen3-tts-12hz-1.7b-customvoice, …) returns HTTP 404 modelnotfound.

Then list the local voice library (JSON to stdout):

edgespeak-cli voices list

Each entry has an id, supported_languages, and a compatibility array naming the models that can use it. Pick an id whose compatibility entry for your chosen model is "ready" — that array, not the voice's name, is the reliable pairing check. The library splits in two:

  • Official named voices — builtin:Vivian, builtin:Serena, builtin:Uncle_Fu, builtin:Dylan,

builtin:Eric, builtin:Ryan, builtin:Aiden, builtin:Ono_Anna, builtin:Sohee. Nine stable identities across ten languages, usable only with the two CustomVoice models. Their names / descriptions objects are empty, so refer to them by id when presenting choices to the user.

  • Cloneable voices — the presets (builtin:bright-girl, builtin:energetic-boy,

builtin:warm-neighbor, …) plus every user:<uuid> the user added. These carry localized names / descriptions (en-US, zh-CN) and work only with the voice_clone models.

Pairing errors

What you sent Response
A CustomVoice model with builtin:auto, a preset, or a user: clone HTTP 400 customvoicerequiresofficialnamed_voice
A voice_clone model with an official named voice HTTP 409 voicenotready
A model id absent from /v1/models (including an invented short alias) HTTP 404 modelnotfound

Recover by re-reading /v1/models and voices list and re-pairing. Never retry the same combination, and if you have to change the user's requested voice or model to make the pair valid, say so.

--instructions is silently ignored by models without instruct. Only Qwen/Qwen3-TTS-12Hz-1.7B-CustomVoice and Qwen/Qwen3-TTS-1.7B-VoiceDesign honor it. Everywhere else the call still returns success with an empty warnings array and byte-identical audio — same seed in, same WAV out. If the user asked for a speaking style, move them to one of those two models rather than reporting a style that was never applied.

Option map

User asks for Use with speech Notes
A specific voice --voice builtin:<id> or --voice user:<uuid> Must be compatible with -m — see "Pick a model and a voice". Default builtin:auto lets the engine pick and is rejected by the two CustomVoice models. OpenAI voice aliases (e.g. alloy) are also accepted on the clone-capable models.
Speaking style ("cheerful", "slow news anchor tone", …) --instructions "<style>" Free-form style text, honored only by models with the instruct feature (Qwen/Qwen3-TTS-12Hz-1.7B-CustomVoice, Qwen/Qwen3-TTS-1.7B-VoiceDesign); silently ignored on every other model. Conflicts with --disable-style.
Ignore the style saved with the voice --disable-style Explicitly disables the voice's default style.
Faster / slower speech --speed <N> Default 1.0. The local model may support a narrower range than OpenAI's 0.25–4.0.
Language hint --language zh-CN or --language en-US Selects the internal reference for the voice.
Reproducible output --seed <N> Non-negative. Same seed + same inputs → same audio. The seed actually used is reported in the result JSON (seed_used).
A different local model -m <model-id> Six local TTS models — see the table in "Pick a model and a voice". Default is k2-fsa/OmniVoice. speech --help lists only three of the six, so read /v1/models, not --help, when choosing.
A specific named voice identity -m Qwen/Qwen3-TTS-12Hz-0.6B-CustomVoice (or the 1.7B one) --voice builtin:<Name> The only way to reach the nine official named voices. The 1.7B variant additionally honors --instructions; the 0.6B variant is faster.
Design a new voice from a description -m Qwen/Qwen3-TTS-1.7B-VoiceDesign --voice builtin:auto --instructions "<voice description>" Voice design invents a voice from free-form text. It requires --voice builtin:auto and --instructions. Short alias qwen3-tts-1.7b-voice-design also works.
Generation quality knobs --guidance-scale <0–5>, --inference-steps <1–64> Omit either for the model default.
Run on a specific compute backend `--device cpu\ cuda\ cuda:<N>\ metal\ auto` Case-insensitive; metal is macOS, gpu means Metal on macOS / CUDA elsewhere. Standalone mode only — with the app gateway reachable the flag errors explicitly; an unavailable backend also errors rather than silently falling back.

Input is limited to 4096 characters per call (OpenAI input limit). For longer text, split it into ≤4096-character parts at natural boundaries (paragraphs/sentences), synthesize each part, and concatenate the WAVs afterwards (ffmpeg -f concat). Keep the same --voice and --seed across parts for a consistent result.

Result JSON (stdout)

Real output shape — long input is synthesized in chunks automatically and reported per chunk:

{
  "output_path": "/abs/path/out.wav",
  "format": "wav",
  "size_bytes": 90284,
  "sample_rate": 24000,
  "duration_seconds": 1.88,
  "seed_used": 3862347868,
  "infer_seconds": 7.49,
  "warnings": [],
  "chunks": [
    { "index": 0, "character_count": 21, "duration_seconds": 1.88,
      "seed_used": 3862347868, "infer_seconds": 7.49, "warnings": [] }
  ]
}

Read sample_rate from the response rather than assuming a fixed rate — it comes from the model. Surface non-empty warnings to the user, but do not treat an empty warnings array as proof that every option took effect: an --instructions string dropped by a model without instruct produces no warning at all.

Voice management

# List all voices (JSON)
edgespeak-cli voices list

# Clone a voice from reference audio + its exact transcript
edgespeak-cli voices add ref.wav --ref-text "<exact words spoken in ref.wav>" \
  --name "My voice" [--language zh-CN] [--speaker-description "<optional description>"] --consent

# Delete a user-created voice (by id or exact name); built-in voices cannot be deleted
edgespeak-cli voices delete user:<uuid>
edgespeak-cli voices delete "My voice"
  • --consent is required for voices add: it asserts the user has permission to use the reference recording. Never add a voice without the user explicitly confirming they have the right to use that recording; refuse to clone third-party voices without consent.
  • --ref-text must be the exact transcript of the reference audio — a mismatch degrades cloning quality.
  • voices delete with a name requires an exact, unique match; ambiguous or unknown names fail with a clear error.
  • After adding, use the returned/listed user:<uuid> id with speech --voice.

MCP and API equivalents

  • Through the EdgeSpeak MCP server (edgespeak-cli mcp or the app's MCP endpoint), the same capabilities are exposed as tools: edgespeakcreatespeech, edgespeaklistvoices, edgespeakaddvoice, edgespeakdeletevoice. Prefer MCP tools when an EdgeSpeak MCP server is already configured. edgespeakcreatespeech accepts the same model ids as the CLI and returns {artifactpath, samplerate, duration, seed_used, chunks[], warnings[]}.
  • Do not take model ids from the MCP schemas. edgespeakcreatespeech's own model description lists an outdated set, and edgespeaklistmodels returns only {id, capabilities, locality, owned_by} — no features. For which model supports named voices, cloning, or instruct, read HTTP /v1/models.
  • With the app running, the local gateway also serves OpenAI-compatible POST /v1/audio/speech (JSON body {model, input, voice, response_format}, WAV bytes back). Stay with the CLI unless the user specifically needs raw API access.

Boundaries / gotchas (read this)

  • Requires edgespeak-cli 0.4.4 or newer (see the version compatibility note up top). Older runtimes ship neither the CustomVoice models nor the official named voices. If a flag documented here is missing from --help, run edgespeak-cli update first.
  • First use needs activation (edgespeak-cli login for browser sign-in — it also upgrades an anonymous trial to your account, activate <KEY> with an existing key, or edgespeak-cli trial for an instant anonymous 7-day trial), same as the other EdgeSpeak skills. Surface license errors; don't work around them. Non-interactive runs fail fast instead of prompting.
  • Six model ids work here, and speech --help only names three of them — see "Pick a model and a voice". Do not conclude a model is unavailable because --help omits it, and do not invent short aliases for the 12Hz models. The app's Broadcast workspace offers the same models with richer UI workflows.
  • Model and voice must match. A mismatch fails fast with customvoicerequiresofficialnamedvoice (400), voicenotready (409), or modelnotfound (404) — recover per "Pairing errors", don't retry unchanged. Some gateway builds additionally reject the CLI's default --voice builtin:auto with HTTP 400 unsupportedauto_voice; the same recovery applies, so prefer choosing an explicit voice upfront over relying on the default.
  • Synthesis is slower than real time on most machines (a short sentence can take ~10–20 s in standalone mode; the first run may also decrypt/load or download the model). Don't assume it hung.
  • Output is WAV only. If the user wants MP3/M4A/OGG, synthesize WAV first and convert with ffmpeg afterwards.
  • stdout vs stderr: the result JSON is on stdout; engine progress/logs are on stderr. Never parse stderr.
  • If speech errors, show the error — do not fabricate audio or claim success without the output file existing.