How do I install the Salute Speech skill?

Run npx skillmds@latest add johnalbertini14-glitch/salute-speech in your terminal (requires Node.js), paste this page's agent-chat prompt into Claude, Cursor, or any MCP-connected agent, or download the SKILL.md file and copy it into your agent's skills directory.

Is Salute Speech safe to use?

This skill has not completed SkillMD's automated safety review yet. Independent scanners report: SkillSpector: PASS, Skill Scanner: PASS. Capability flags: executes scripts, makes network calls, reads secrets. SkillMD never runs a skill's scripts for you; review the SKILL.md before installing.

Which AI agents work with Salute Speech?

This skill is tagged as working with Claude Code, Claude.ai, OpenAI Codex. SKILL.md is an open format, so most agents that read a skills directory can load it too.

Is Salute Speech free to use?

Yes. Installing skills from SkillMD is free, and the skill stays under its author's original license.

Who published Salute Speech?

johnalbertini14-glitch (@johnalbertini14-glitch) published this skill. Their other Agent Skills are listed on their SkillMD profile.

Salute Speech by johnalbertini14-glitch

Name: Salute Speech
Rating: 4.666666666666667 (3 reviews)
Author: johnalbertini14-glitch

File contents

Audio Transcription with Sber Salute Speech

Transcribe audio/video files to text with timestamps via Salute Speech async REST API.

Requirements

API Key: Environment variable SALUTE_AUTH_DATA must be set (Base64-encoded client_id:client_secret or raw authorization key from https://developers.sber.ru/studio/).
SSL note: The script disables SSL verification by default (verify_ssl=False) because Sber's certificate chain is non-standard. This is expected.

Supported formats & encodings

Audio encoding	Content-Type	Typical extensions
`MP3`	`audio/mpeg`	`.mp3`
`PCM_S16LE`	`audio/wav`	`.wav`
`OPUS`	`audio/ogg`	`.ogg`, `.opus`
`FLAC`	`audio/flac`	`.flac`
`ALAW`	`audio/alaw`	`.alaw`
`MULAW`	`audio/mulaw`	`.mulaw`

Supported languages

ru-RU, en-US, kk-KZ (Kazakh), ky-KG (Kyrgyz), uz-UZ (Uzbek).

Workflow

Identify input files — from user request.
Read API key from host environment.
Run transcription — execute salute_transcribe.py with uv and appropriate arguments.
Deliver results — present to user human-readable transcript with timestamps to the user and give a direct link to files.

Usage

uv run --with requests {baseDir}/salute_transcribe.py \
  --file /path/to/audio.mp3 \
  --output_dir ~/.openclaw/workspace/transcriptions \
  --lang ru-RU

Arguments

Argument	Required	Default	Description
`--file`	Yes	—	Path to audio/video file
`--output_dir`	No	`~/.openclaw/workspace/transcribations`	Output directory for results
`--lang`	No	`ru-RU`	Language code: `ru-RU`, `en-US`, `kk-KZ`, `ky-KG`, `uz-UZ`
`--audio-encoding`	No	`MP3`	Codec: `MP3`, `PCM_S16LE`, `OPUS`, `FLAC`, `ALAW`, `MULAW`
`--model`	No	`general`	Recognition model: `general` or `callcenter`
`--hyp-count`	No	`1`	Number of alternative hypotheses: `1` or `2`
`--max-wait-time`	No	`300`	Max seconds to wait for async result
`--print`	No	off	Also print transcription to stdout

Content-Type mapping

When the file extension doesn't match audio/mpeg, adjust content_type in the script or add logic. Current default is audio/mpeg (MP3). For .wav files use audio/wav, etc.

Output files

For input file meetingABC.mp3 the script produces:

File	Description
`meetingABC_recognition_orig.json`	Raw API response (full JSON with all hypotheses, timing, confidence)
`meetingABC_pretty.txt`	Formatted human-readable transcript with timestamps

Output text format

[00:01 - 00:20]:
Ну, даже если сосредоточиться на идее узкой щели.

[00:20 - 00:45]:
Следующий фрагмент текста здесь.

Notes

Token is valid for ~30 minutes; the script fetches a new one each run.
Large files (>1 hour) may need --max-wait-time increased beyond 300s.
The callcenter model is optimized for telephony audio (8kHz, mono).
Profanity filter is disabled by default (enable_profanity_filter=False).
The script uses normalized text by default (numbers as digits, abbreviations expanded). Raw text is also available in the JSON output.

---name: salute-speechdescription: Transcribe audio files using Sber Salute Speech async API. Russian-first STT with support for ru-RU, en-US, kk-KZ, ky-KG, uz-UZ.--- # Audio Transcription with Sber Salute Speech Transcribe audio/video files to text with timestamps via Salute Speech async REST API. ## Requirements - **API Key**: Environment variable `SALUTE_AUTH_DATA` must be set (Base64-encoded `client_id:client_secret` or raw authorization key from https://developers.sber.ru/studio/). - **SSL note**: The script disables SSL verification by default (`verify_ssl=False`) because Sber's certificate chain is non-standard. This is expected. ## Supported formats & encodings | Audio encoding | Content-Type | Typical extensions | |---------------|-------------|--------------------| | `MP3` | `audio/mpeg` | `.mp3` | | `PCM_S16LE` | `audio/wav` | `.wav` | | `OPUS` | `audio/ogg` | `.ogg`, `.opus` | | `FLAC` | `audio/flac` | `.flac` | | `ALAW` | `audio/alaw` | `.alaw` | | `MULAW` | `audio/mulaw` | `.mulaw` | ## Supported languages `ru-RU`, `en-US`, `kk-KZ` (Kazakh), `ky-KG` (Kyrgyz), `uz-UZ` (Uzbek). ## Workflow 1. **Identify input files** — from user request. 2. **Read API key** from host environment. 3. **Run transcription** — execute `salute_transcribe.py` with `uv` and appropriate arguments. 4. **Deliver results** — present to user human-readable transcript with timestamps to the user and give a direct link to files. ## Usage ```bash uv run --with requests {baseDir}/salute_transcribe.py \ --file /path/to/audio.mp3 \ --output_dir ~/.openclaw/workspace/transcriptions \ --lang ru-RU ``` ### Arguments | Argument | Required | Default | Description | |----------|----------|---------|-------------| | `--file` | **Yes** | — | Path to audio/video file | | `--output_dir` | No | `~/.openclaw/workspace/transcribations` | Output directory for results | | `--lang` | No | `ru-RU` | Language code: `ru-RU`, `en-US`, `kk-KZ`, `ky-KG`, `uz-UZ` | | `--audio-encoding` | No | `MP3` | Codec: `MP3`, `PCM_S16LE`, `OPUS`, `FLAC`, `ALAW`, `MULAW` | | `--model` | No | `general` | Recognition model: `general` or `callcenter` | | `--hyp-count` | No | `1` | Number of alternative hypotheses: `1` or `2` | | `--max-wait-time` | No | `300` | Max seconds to wait for async result | | `--print` | No | off | Also print transcription to stdout | ### Content-Type mapping When the file extension doesn't match `audio/mpeg`, adjust `content_type` in the script or add logic. Current default is `audio/mpeg` (MP3). For `.wav` files use `audio/wav`, etc. ## Output files For input file `meetingABC.mp3` the script produces: | File | Description | |------|-------------| | `meetingABC_recognition_orig.json` | Raw API response (full JSON with all hypotheses, timing, confidence) | | `meetingABC_pretty.txt` | Formatted human-readable transcript with timestamps | ### Output text format ``` [00:01 - 00:20]: Ну, даже если сосредоточиться на идее узкой щели. [00:20 - 00:45]: Следующий фрагмент текста здесь. ``` ## Notes - Token is valid for ~30 minutes; the script fetches a new one each run. - Large files (>1 hour) may need `--max-wait-time` increased beyond 300s. - The `callcenter` model is optimized for telephony audio (8kHz, mono). - Profanity filter is disabled by default (`enable_profanity_filter=False`). - The script uses **normalized text** by default (numbers as digits, abbreviations expanded). Raw text is also available in the JSON output.

Frequently asked questions

Salute Speech