--- name: kesha-voice-kit description: Local multilingual voice toolkit — speech-to-text (STT), text-to-speech (TTS), and language detection. Runs entirely offline on Apple Silicon, Linux, and Windows. No API keys, no cloud. NVIDIA Parakeet TDT for STT across 25 European languages, Kokoro-82M + Vosk-TTS for TTS, plus macOS AVSpeechSynthesizer for ~180 system voices with zero install. emoji: 🎙️ requires: bins: [kesha] install: - kind: bash cmd: bun add -g "@drakulavich/kesha-voice-kit" - kind: bash cmd: kesha install --- # kesha-voice-kit Local voice toolkit: transcribe voice messages to text, synthesize speech, detect language of audio or text. Fully offline after `kesha install`. No API keys, no per-minute billing. **Trigger keywords for when to use this skill:** voice message, voice memo, voice note, .ogg, .opus, .wav, .mp3, audio file, transcribe, transcription, speech-to-text, STT, text-to-speech, TTS, synthesize speech, say, telegram voice note, whatsapp voice note, ogg-opus, opus, multilingual voice, multilingual ASR, language detection, offline voice, privacy, Apple Silicon, CoreML. ## When to use - **Voice memo arrived** (Telegram, WhatsApp, Slack, Signal .ogg/.opus/.m4a): transcribe with `kesha --json ` and branch on the detected language. - **Need to send a voice note (Telegram, WhatsApp, Signal, Discord)**: synthesize directly into messenger-native OGG/Opus with `kesha say --format ogg-opus --out reply.ogg ""`. Default is mono 24 kHz @ 32 kbps - what Telegram `sendVoice` expects. No WAV redirect and no `ffmpeg` round-trip. - **Need local file playback/debug output**: WAV is still available with `kesha say --out reply.wav ""`, but do not use WAV for Telegram voice replies. Auto-routes by detected language (Kokoro-82M for English, Vosk-TTS for Russian). On darwin-arm64, English Kokoro uses FluidAudio CoreML instead of ONNX. For other languages and ~180 more voices use `--voice macos-*` on macOS (zero model download). - **Need to detect what language a file is in** before choosing a pipeline: `kesha --json audio.ogg` returns both audio-based and text-based language detection with confidence scores. ## OpenClaw plugin setup Install the plugin, then explicitly route OpenClaw audio understanding through the CLI model entry. The plugin registration makes Kesha discoverable, but real voice-message transcription uses `tools.media.audio.models` with a `type: "cli"` entry. ```bash bun add -g @drakulavich/kesha-voice-kit kesha install openclaw plugins install @drakulavich/kesha-voice-kit openclaw config patch --stdin <<'JSON5' { tools: { media: { audio: { enabled: true, models: [ { type: "cli", command: "kesha", args: ["{{MediaPath}}"], timeoutSeconds: 15, }, ], echoTranscript: true, echoFormat: '🦜 "{transcript}"', }, }, }, } JSON5 ``` Use Kesha's default output for OpenClaw's normal voice-message path: stdout is the bare transcript text, while progress and errors stay off the transcript payload. The default setup echoes each transcript back to chat as `🦜 "{transcript}"` before the agent responds. For agents that need timestamped segments, switch the model entry to JSON output and allow a longer timeout: ```bash openclaw config set tools.media.audio.models \ '[{"type":"cli","command":"kesha","args":["--json","--timestamps","{{MediaPath}}"],"timeoutSeconds":30}]' ``` Verification checklist: ```bash which kesha kesha status openclaw plugins list openclaw config get tools.media.audio.models openclaw config get tools.media.audio.echoTranscript openclaw config get tools.media.audio.echoFormat ``` Do not rely on `openclaw.plugin.json` to patch `tools.media.audio.models`; OpenClaw ignores non-schema fields such as `configPatch`. Keep the CLI route in user config. For OpenClaw TTS replies, route the local TTS provider to Kesha OGG/Opus output. This is the Telegram-safe path: ```bash openclaw config patch --stdin <<'JSON5' { messages: { tts: { auto: "always", provider: "tts-local-cli", providers: { "tts-local-cli": { command: "kesha", args: ["say", "--format", "ogg-opus", "--out", "{{OutputPath}}", "{{Text}}"], outputFormat: "opus", timeoutMs: 120000, }, }, }, }, } JSON5 ``` When invoking Kesha manually from an OpenClaw flow, write OGG/Opus into an OpenClaw-owned temp path, for example `kesha say --format ogg-opus --out /tmp/openclaw/reply.ogg ""`, after ensuring the directory exists. The configured `tts-local-cli` provider should use OpenClaw's `{{OutputPath}}` placeholder instead of a hardcoded path. Do not configure OpenClaw Telegram TTS as `kesha say "" > reply.wav`; that creates a WAV file and will not render as a native Telegram voice note. ## STT: transcribe audio ```bash # JSON output with language detection (recommended for automation) kesha --json voice.ogg ``` ```json [{ "file": "voice.ogg", "text": "Привет, как дела?", "lang": "ru", "audioLanguage": { "code": "ru", "confidence": 0.98 }, "textLanguage": { "code": "ru", "confidence": 0.99 } }] ``` Use `lang` (or the more detailed `audioLanguage`/`textLanguage`) to decide how to respond. Need timestamped transcript segments for navigation, chapters, or downstream editing: ```bash kesha --json --timestamps voice.ogg > voice.timestamps.json jq '.[0].segments' voice.timestamps.json ``` Each segment has `start`, `end`, and `text` fields. `--timestamps` is available for machine-readable output (`--json`, `--toon`, or `--format json`). **Speaker diarization** (darwin-arm64, post-v1.12.0). Add `--speakers` to label each segment with a cluster ID — useful for transcribing multi-person calls / meetings: ```bash kesha install --diarize # one-time, ~245MB kesha --json --vad --speakers meeting.m4a > out.json jq '.[0].segments[] | "\(.speaker)\t\(.text)"' out.json ``` Each `segment.speaker` is a number (cluster id, stable within one file). On Linux / Windows the engine returns a clear "currently darwin-arm64 only" error — see [#199](https://github.com/drakulavich/kesha-voice-kit/issues/199). **Formats:** .ogg, .opus, .mp3, .m4a, .wav, .flac, .webm — decoded via symphonia, no ffmpeg required. **Other output modes:** - `kesha audio.ogg` — plain transcript on stdout - `kesha --format transcript audio.ogg` — transcript + `[lang: ru, confidence: 0.99]` footer - `kesha --json --timestamps audio.ogg` — JSON with timestamped `segments` - `kesha --verbose audio.ogg` — human-readable with language info - `kesha --lang en audio.ogg` — warn if detected language differs (useful sanity check) ## TTS: synthesize speech ```bash kesha say "Hello, world" > hello.wav # auto-routes en → Kokoro-82M kesha say "Привет, мир" > privet.wav # auto-routes ru → Vosk-TTS kesha say --voice macos-de-DE "Guten Tag" > de.wav # any macOS system voice — German, French, Italian, ... kesha say --list-voices # Kokoro + Vosk-TTS + ~180 macos-* voices ``` Output: WAV mono float32 by default. `--out ` writes to a file instead of stdout. For Telegram/OpenClaw replies, prefer `--format ogg-opus --out reply.ogg` or the OpenClaw-provided `{{OutputPath}}`. **Voice notes (Telegram / WhatsApp / Signal / Discord):** add `--format ogg-opus` to emit OGG/Opus directly — the format messenger APIs render as a native voice message: ```bash kesha say --format ogg-opus --out reply.ogg "Hello there" # 24 kHz @ 32 kbps mono - Telegram-grade kesha say --voice ru-vosk-m02 --format ogg-opus --out reply.ogg "Привет" # Russian voice note kesha say --format ogg-opus --bitrate 16000 --out tiny.ogg "Hi" # tinier file, intelligible but lossy ``` Format is also inferred from `--out` extension (`.ogg` / `.opus` / `.oga` → OGG/Opus). `--bitrate` (6 000–510 000 bps) and `--sample-rate` (8 000 / 12 000 / 16 000 / 24 000 / 48 000 Hz) tune the encoder. **Russian abbreviations** (`ru-vosk-*`): all-uppercase Cyrillic 2-5-char tokens auto-expand letter-by-letter when not pronounceable as a Russian syllable (ФСБ → "эф-эс-бэ", ВОЗ → "воз"). Disable with `--no-expand-abbrev`. See [docs/tts.md#russian-abbreviation-auto-expansion](docs/tts.md#russian-abbreviation-auto-expansion). **English acronyms** (`en-*`, Kokoro): three-table mechanism (letter-spell rule + STOP_LIST + IPA_LEXICON) auto-expands FBI → "ef bee eye" and gives EPAM/JSON/Anthropic the right IPA. Disable letter-spell with `--no-expand-abbrev`. See [docs/tts.md#english-acronym-auto-expansion](docs/tts.md#english-acronym-auto-expansion). **Russian word stress** (`ru-vosk-*` only): `сл+ово` shifts stress to the vowel marked with `+`. `сл+ово` strips the `+` (cancel inherited emphasis). Other voices (`en-*`, `macos-*`) silently strip the `+` and warn once per process. Auto-stress dictionary not provided — caller writes the `+` manually. Closes [#233](https://github.com/drakulavich/kesha-voice-kit/issues/233). **Speech rate via SSML** (`ru-vosk-*` and `en-*` voices): wrap the utterance in `` to slow down or speed up synthesis. Supports SSML named values (`x-slow`/`slow`/`medium`/`fast`/`x-fast`), absolute `N%` (e.g. `120%`), and relative `+N%`/`-N%`. Honored only when `` wraps the whole utterance — mid-utterance prosody warns and synthesizes at default rate. `--rate` and `` compose multiplicatively; result is clamped to 0.5×–2.0×. AVSpeech (`macos-*` voices) does not yet accept SSML — see [#236](https://github.com/drakulavich/kesha-voice-kit/issues/236). ## Language detection standalone `kesha --json audio.ogg` includes both audio-based (`audioLanguage`) and text-based (`textLanguage`) detection. Use audio detection to identify the language before running language-specific logic. ## Install ```bash bun add -g @drakulavich/kesha-voice-kit # global CLI install kesha install # downloads engine (~350 MB) kesha install --tts # adds Kokoro + Vosk-TTS RU (~990 MB more, for TTS) ``` No system deps — English G2P is embedded (`misaki-rs`); Russian G2P is bundled inside Vosk-TTS. `macos-*` voices need no install either — they use voices already on the Mac. ## Supported languages **Speech-to-text (25):** Bulgarian, Croatian, Czech, Danish, Dutch, English, Estonian, Finnish, French, German, Greek, Hungarian, Italian, Latvian, Lithuanian, Maltese, Polish, Portuguese, Romanian, Russian, Slovak, Slovenian, Spanish, Swedish, Ukrainian. **Text-to-speech:** English (Kokoro-82M; FluidAudio CoreML on darwin-arm64, ONNX elsewhere), Russian (Vosk-TTS, 5 baked-in speakers — default `ru-vosk-m02`), plus any macOS system voice via `--voice macos-*`. ## Performance - ASR: ~19× faster than OpenAI Whisper on Apple Silicon (CoreML via FluidAudio), ~2.5× on CPU (ONNX via `ort`). - TTS: sub-second latency for short utterances on Apple Silicon. ## Why local No API keys to manage. No per-minute billing. Voice data never leaves the machine — important for regulated industries, personal messaging, and anything that shouldn't be in a third-party log. ## Links - Source: https://github.com/drakulavich/kesha-voice-kit - npm: https://www.npmjs.com/package/@drakulavich/kesha-voice-kit - Releases: https://github.com/drakulavich/kesha-voice-kit/releases

Kesha Voice Kit

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