YazSes

Offline voice typing for Linux, macOS and Windows. Hold a key, speak, release, and your words are typed into whatever app you are using.

Speech recognition runs on your own computer, so your voice never leaves it. There is no account, no subscription and no API key. YazSes is free and open source under Apache 2.0.

A 40-second tour of dictation, the command line and the system tray. The terminal output is real; the command-line typing was re-enacted so it is easier to read. ▶️ Watch it on YouTube, with chapters.

Install · Quick start · Voice commands · Compare · FAQ · Documentation · Contribute

✨ What it does

Also included: multi-step voice macros and a personal vocabulary for words it mishears · Dysfluency-Friendly Mode, which collapses stutters and repeats (b-b-because → because) · opt-in, encrypted on-device learning, where yazses tune proposes accuracy fixes from your own corrections · editor navigation through your editor's LSP (yazses jump, Neovim bridge, opt-in) · EMG (muscle-sensor) triggering and mic calibration for accessibility · an optional voice-activity overlay near the cursor. The feature catalog lists every capability and how to turn it on.

What's optional: dictation works out of the box. Speaker labels need the diarization extra (pipx install 'yazses[diarization]', ~45 MB of models, downloaded once). Meeting minutes also need the notes extra and a local GGUF model that you supply. Both are off by default. See offline meeting notes.

⬇️ Install

Choose your operating system. Each install is one command followed by a short first-run setup.

🐧 Linux (the most tested platform)

bash <(curl -fsSL https://raw.githubusercontent.com/MSKazemi/yazses/main/install.sh)

Then log out and back in once, which gives YazSes access to the keyboard, and run yazses start. Full Linux guide →

🍎 macOS, Apple silicon (M1 or newer) (preview)

brew tap MSKazemi/yazses && brew trust MSKazemi/yazses && brew install --cask yazses

Open YazSes from Applications. The app is not signed yet, so macOS blocks it the first time: click Open Anyway in System Settings → Privacy & Security, then allow Microphone, Accessibility and Input Monitoring when asked. On an Intel Mac, download the -macos-x86_64.dmg from Releases instead. Releases after 2.43.2 put a yazses command on your PATH through the Homebrew cask; with the .dmg, or on 2.43.2, run the CLI as /Applications/YazSes.app/Contents/MacOS/YazSes --cli doctor. Full macOS guide →

🪟 Windows (preview)

winget install MSKazemi.YazSes

winget can lag behind the newest release; the installer, Scoop and Chocolatey track every release. The installer is not code-signed yet, so if Windows SmartScreen warns you, click More info → Run anyway. Then open YazSes from the Start menu. Full Windows guide →

Then start talking. Hold your hotkey, speak and release. The default hotkey is Right Alt on Linux, Right Option on macOS and Right Ctrl on Windows; yazses hotkey set <key> changes it. If nothing happens, run yazses doctor. It checks your microphone, hotkey and typing, and tells you what to fix.

macOS and Windows are previews. Linux has the most reports from real machines. The macOS and Windows builds are newer, and the validation matrix shows exactly what has and has not been confirmed on real hardware. If you try one, a short report is one of the most useful contributions you can make.

Not ready to install? Try it without installing in Docker or your browser, or read what installing actually costs first. APT, Snap, pipx, .dmg and .exe are covered under all install options.

🙌 Help build YazSes

New to open source? You are welcome here. You need no speech or AI background, and several tasks need no Python at all:

• Test it on your computer and report what happened.
• Translate or review the README in your language.
• Add your microphone to the known-good list.
• Write code: pick a good first issue. The test suite is fully offline, so you need no microphone, model or GPU.

Start here: one page where you pick the row that matches what you have and finish in 15–45 minutes. No permission is needed and nothing is assigned. #22 lists everything open, and Contributing below covers the development workflow.

⭐ If YazSes is useful to you, a star is how other people find it. There is no company and no advertising budget behind this project; word of mouth is how it reaches people.

About YazSes

YazSes is a free, open-source, offline voice dictation and speech-to-text daemon for Linux (X11 and Wayland), macOS and Windows, built on faster-whisper. Use it when audio must not be sent to Google, Apple, Microsoft or Otter: because the meeting is confidential, because the machine is air-gapped, or because you do not want a subscription.

• Compared with cloud dictation such as Wispr Flow, YazSes runs entirely on-device.
• Compared with Talon Voice, it aims at plug-and-play use rather than advanced scripting.
• Compared with other free on-device tools (Handy, OpenWhispr), it adds voice commands, speaker-labelled meeting capture and published benchmarks.
• It is not the right tool if you need a conversational AI agent, non-English models out of the box, or a mobile or web app.

📖 Full documentation: mskazemi.com/yazses, with install guides, the CLI reference, configuration, features and troubleshooting.

Prefer text to video? Watch the CLI in your browser: an asciinema recording of the happy path (-h → about → quickstart → features → status) in which every byte is real command output. The player is served from the docs site itself, not a CDN, so watching it does not report you to anyone. In your own terminal, run asciinema play docs/demo/yazses-cli.cast.

Quick Start

Want to hear how accurate it is first? Try it without installing in Docker or your browser. A sample clip ships with the repository, and --network none proves the transcription happens on your own machine.

Step 1 — Install

Use the command for your system in Install above, or any route in all install options.

The recommended Linux one-liner installs uv if needed, installs the latest YazSes, sets up every system prerequisite (audio, keystroke injection, clipboard, the input group and Wayland ydotoold), and finishes by running yazses doctor so that any missing tool shows up during the install rather than later.

Wary of piping a script from the internet into your shell? Add --dry-run. The script inspects your machine, prints every change it would make, and exits without making any: bash <(curl -fsSL .../install.sh) --dry-run

Both what installing actually costs (1.1 GB plus a 141 MB model, and what it changes on your system) and how to uninstall are published up front.

Only need to transcribe a recording? The container needs no install at all: docker run --rm -v "$PWD:/data" ghcr.io/mskazemi/yazses transcribe /data/talk.m4a --diarize. It produces a transcript with speaker labels. It does not do hold-to-talk dictation, which needs a real desktop session; see the Docker page.

Step 2 — Prepare the system (Linux only)

The one-liner and the APT install do this for you, and the Snap does not need it. After a pipx or source install, run:

yazses setup        # installs audio + injection deps, joins the input group, sets up ydotoold
# then log out and back in (the input-group change needs a fresh login)

yazses setup is safe to re-run and only does what is missing. It ends with a numbered checklist of the steps only you can do (the re-login, voice calibration with yazses mic-level --set, and yazses start) and offers to run the calibration right away.

The log-out and log-in is required, once. Joining the input group only takes effect in a new login session. Opening another terminal tab is not enough, because it inherits the old session's groups and the hotkey stays dead. yazses start warns you while the re-login is still pending. To dictate immediately without logging out, bridge the group for one session with sg input -c "yazses restart".

On macOS and Windows, skip this step and grant the Accessibility and Microphone permissions when prompted.

Step 3 — Calibrate and start

yazses quickstart           # not sure what's next? a 3-step guide tailored to your machine
yazses doctor               # check mic, injection backend, permissions (want all [OK])
yazses mic-level --set      # tune the silence gate to your room and voice (~6 s)
yazses enroll               # optional: a longer guided calibration (20 short phrases)
yazses autostart enable     # run it at login, so it's there after a reboot
yazses start                # start the dictation daemon
yazses verify               # speak once and prove the whole pipeline works

yazses quickstart is safe to run at any time. It looks at what is already set up, tells you what to do next, and changes nothing.

Step 4 — Dictate

Hold the hotkey, speak and release. The text is typed into the focused app.

Try "the quick brown fox" (typed as text), then "undo that", "go to line 42" or "run the tests" (carried out as commands). On a modern laptop CPU, the time from releasing the key to seeing text is a median of 1.6 s with the default base.en model, or 0.9 s with tiny.en (measured).

Shell completion: yazses --install-completion, or yazses --show-completion to print the script. See the CLI reference.

What you can say

Hold the key and talk: by default, everything you say is typed at the cursor. YazSes also recognises a set of voice commands and turns them into editor and terminal key sequences instead of typing them:

Commands are recognised by a fast regex grammar. You can add multi-step macros and a personal vocabulary of misheard words; see the CLI reference.

How it works

Hold hotkey → record audio → VAD gate → faster-whisper (CPU) → clean + disfluency filter
            → command grammar (Tier 1 regex; Tier 2 SLM router designed, not wired)
            → dictate? type the text   ·   command? send the key sequence

Everything runs on your CPU, with no GPU and no network. faster-whisper (int8) transcribes the audio, and a regex grammar decides whether each utterance is dictation or a command. A ~0.5B SLM router was designed to take a second look when confidence is low. Its seam exists (grammar.classify() accepts one), but nothing constructs it yet, so the regex grammar decides every utterance today.

Performance. Measured on a 13th-gen Core i7 laptop, int8 on CPU: 4.07 % WER on LibriSpeech test-clean with the default base.en, a 1.56 s median decode, and 0.29 ms of total non-decode pipeline overhead. Almost all of the latency is the speech model. The method and the commands to reproduce these numbers are on the benchmarks page.

Models

• Speech-to-text: faster-whisper tiny.en (fastest), base.en (default) or small.en (most accurate), int8 on CPU.
• Dictation cleanup (optional, off by default): a small offline LLM can tidy grammar and punctuation. Length and token-preservation guards stop it from changing your meaning.
• Command routing (not wired yet): a Qwen2.5-0.5B SLM for Tier 2 intent classification. yazses model download can fetch it, but nothing loads it yet, so downloading it today gains you nothing. The command is still the right way to pre-fetch a speech model behind a firewall.

Requirements

Using Apple silicon, an Intel Mac, ARM64 Windows, a Raspberry Pi or another less common CPU? The platform support matrix lists the tested install channel for each OS and architecture. pipx install yazses is a portable fallback on supported Python and platform combinations, but a native package gives a better desktop experience where one exists.

Use cases

Guides with setup steps: voice typing on Linux (X11 and Wayland) · voice dictation on Wayland · dictation over SSH and Remote-SSH · private and confidential work · coding by voice · accessibility and RSI · transcribing recordings · multilingual dictation

Limitations / when not to use YazSes

• It is not an LLM agent. YazSes dictates text, transcribes recordings and runs editor and terminal commands. It does not browse, reason over your files or hold a conversation (it can set an offline timer by voice, opt-in); that was the paused Rust exploration.
• Speaker labels and minutes are extras, not defaults. --diarize and meeting minutes each need an opt-in extra, and minutes also need a local GGUF model that you supply. Plain dictation and plain transcription need neither.
• It uses faster-whisper on the CPU, not a cloud service. On a noisy microphone, a cloud speech service may still achieve a lower word-error rate. The trade-off is that nothing leaves your machine.
• It is tuned for English by default. It ships with *.en Whisper models; other languages need a different model.
• It is desktop only, for now. There is no mobile or web build. An Android app is in design: the architecture and its ten decision records are public at docs/mobile, and contributors are building it in the open. iOS and iPadOS will follow Android.

Comparison & alternatives

An honest comparison with other voice-dictation tools. Every claim is about publicly documented behaviour, and each tool has strengths YazSes does not.

Preview means supported and installable, but not yet verified on hardware by a person on a current build; the validation matrix shows what testers have confirmed so far.

The open-source, local, free ones

A growing group of tools shares YazSes's licence model and privacy model. Leaving them out would make this comparison evasive to exactly the readers who already know about them.

Handy is the closest alternative. It is MIT-licensed, free, cross-platform and on-device, with the same hold-a-key-and-speak loop. If you want dictation and nothing else, it is an excellent choice and considerably smaller than YazSes.

Good reasons to choose another tool:

• Handy: you want dictation only, with the smallest possible install.
• OpenWhispr: you want a polished Electron app, and falling back to a cloud model with your own API key is a feature for you rather than a dealbreaker.
• FluidVoice: you are on macOS and want voice control of the OS itself (launching apps, running Shortcuts), which goes beyond YazSes's editor-oriented commands.
• VoiceInk: you are on macOS, want a native app, and prefer paying once.
• Talon Voice: you want deep, scriptable voice control and are willing to learn its scripting model. YazSes and Talon can run side by side.
• Windows Voice Access: you are on Windows 11 and want zero install and OS integration.
• Dragon: you want a mature, professionally supported Windows product and can pay for it.
• Wispr Flow: you prefer a polished cloud service and are comfortable sending audio off-device.

So what is actually different about YazSes?

Being open source, local, cross-platform and free no longer sets YazSes apart: Handy and OpenWhispr are all four. The real differences are narrower:

1. Voice commands as well as dictation, with a documented grammar. Most of the tools above do dictation only.
2. Linux as a first-class target, not a port: X11 and Wayland injection, evdev hold-to-talk, systemd autostart, a .deb, an APT repository and a snap.
3. Meeting capture with speaker labels, entirely on-device.
4. Published benchmarks with a stated method, plus an explicit list of what was not measured. See benchmarks.
5. Accessibility as a design constraint, not an add-on: dysfluency-friendly filtering, calibrated silence gates, and activation that does not depend on a keyboard.

How current is this? It was compiled from each project's own documentation in August 2026, not from testing each tool. This space moves quickly. If a row is out of date, tell us; a comparison that flatters us by being stale is worth less than no comparison at all.

FAQ

What is YazSes? An open-source, offline hold-to-talk voice-dictation daemon for Linux, macOS and Windows. You hold a key, speak and release; your speech is transcribed on-device with faster-whisper and typed into the focused application. It also supports editor and terminal voice commands and macros.

Is there a good offline voice-dictation tool for Linux? Yes. YazSes runs natively on Linux (X11 and Wayland), transcribes locally on the CPU, and needs no cloud service or API key. It installs with a one-line script, APT, Snap or pipx.

How does YazSes compare with Talon? Both are cross-platform and work offline. YazSes focuses on plug-and-play dictation plus a practical command grammar. Talon offers far more advanced, scriptable voice control. You can use them side by side.

Does it work without internet? Yes. Transcription runs locally with faster-whisper, and by default no audio or text is sent anywhere. YazSes works fully offline, including on air-gapped machines.

Is it free and open source? Yes. YazSes is released under the Apache 2.0 licence, with no subscription or API key.

What hardware do I need? No GPU. It runs on the CPU with 4 GB of RAM at minimum (8 GB is comfortable) and any USB or built-in microphone.

Is it an AI agent? No. YazSes dictates text and runs editor and terminal voice commands; it does not browse, reason over your files or hold a conversation. An agentic version was prototyped in the archived Rust branch but has not shipped.

More in the full FAQ and the side-by-side comparison page (YazSes vs Talon, Dragon, Wispr Flow, nerd-dictation and others).

CLI commands

The most common commands. Run yazses --help, or see the CLI reference, for everything else.

Configuration

The settings file lives here:

You rarely need to edit it by hand. yazses features, yazses hotkey and yazses vocab change it safely and keep your comments. The essential settings are:

[stt]
model = "base.en"           # tiny.en (fast) | base.en | small.en (accurate); CPU int8
initial_prompt = ""         # vocabulary/context primed into Whisper

[hotkey]
key = "auto"                # hold-to-talk key; "auto" = Right Alt on Linux,
                            # Right Option on macOS, Right Ctrl on Windows
                            # (yazses hotkey set <key>)
command_key = ""            # optional dedicated key that forces command mode
hold_threshold_ms = 500     # how long to hold before recording starts

[audio]
sample_rate = 16000
max_record_seconds = 300    # a single hold is cut at this many seconds

[injection]
backend = "auto"            # auto | type | ydotool | wtype | clipboard
                            # ("xdotool" is not a token — on X11 `auto` already
                            #  uses xdotool; asking for it on Wayland gets ydotool)

[accessibility]
vad_threshold = 0.01        # lower for quiet speech, raise if room noise triggers (yazses mic-level --set)

Every option is documented in the configuration reference and in examples/config.example.toml.

Microphone not working?

If YazSes does nothing and the log shows Silent audio -- discarding, your speech is below the voice-activity threshold. Measure your voice, set the threshold, and restart:

yazses mic-level --set   # measure your voice and set the right threshold
yazses restart

All install options

Upgrading

pipx install yazses always installs the latest published release from PyPI. To upgrade an existing install in place:

pipx upgrade yazses          # upgrade an existing install to the latest release
pipx install --force yazses  # reinstall the latest (if upgrade reports "already at latest")

To pin an exact version, use pipx install yazses==2.15.0. Check what you have with:

yazses --version

yazses doctor also reports the version of the running daemon.

Linux

APT (Debian and Ubuntu). This tracks tagged releases; the one-line installer above remains the recommended route.

bash <(curl -fsSL https://raw.githubusercontent.com/MSKazemi/yazses/main/install-apt.sh)

pipx (any distribution with Python ≥ 3.11):

sudo apt install pipx build-essential python3-dev   # evdev is compiled from source
pipx install 'yazses[desktop]'                      # [desktop] adds the tray + overlay (Qt)
yazses setup                                        # audio/injection deps, input group, ydotoold
# then log out and back in once (the input-group change needs a new login)

Snap works on X11, and on GNOME and KDE Wayland through the xdg-desktop-portal RemoteDesktop API. Both snap connect lines are required. A snap cannot connect its own interfaces, and without them the daemon starts and looks healthy but never hears you or never sees the key. See what the snap can and cannot do.

sudo snap install yazses
sudo snap connect yazses:audio-record   # microphone; without it, no audio
sudo snap connect yazses:raw-input      # hold-to-talk key; without it, nothing fires
yazses doctor                           # says if anything is still missing
yazses start

A Snap install does not need yazses setup. Strict confinement stops it from changing host packages, groups or services, so current builds only use it to print the manual permission checklist; the snap already bundles its X11 dependencies. Run yazses doctor and every other YazSes command as your normal desktop user, never through sudo.

From source (for contributors). One command does the whole loop: an editable install, yazses setup provisioning, and a start that bridges the input group so you can test before logging out.

bash scripts/dev-install.sh

macOS

# Homebrew — Apple Silicon only (see below)
brew tap MSKazemi/yazses
brew trust MSKazemi/yazses          # required: Homebrew now gates third-party taps
brew install --cask yazses

# pipx — Apple Silicon: Python ≥ 3.11.  Intel: Python 3.11–3.13 (see below)
pipx install yazses

# App bundle (.dmg) — unsigned developer preview; separate Apple Silicon and Intel builds
# https://github.com/MSKazemi/yazses/releases/latest

On an Intel Mac, use the -macos-x86_64.dmg or pipx, not Homebrew. Since v2.22.0 each release carries both …-macos-arm64.dmg and …-macos-x86_64.dmg. The Homebrew cask is still Apple silicon only: it declares arch: :arm64 and refuses to install rather than installing a broken app. Details in docs/macos-install.md.

⚠ Intel Macs have a Python ceiling set upstream. pipx install yazses needs Python 3.11–3.13 there, and yazses[all] needs 3.11–3.12, because upstream stopped building Intel macOS wheels: onnxruntime published none after 1.23.2 (which has no Python 3.14 build) and torch none after 2.4.1 (no 3.13 build). On Python 3.14 the install fails with a resolver error naming onnxruntime. It looks like a YazSes bug but is not one. On an Intel Mac, yazses doctor shows where you stand against this ceiling, so you learn about it before an upgrade. Apple silicon is unaffected.

Windows

winget install MSKazemi.YazSes                  # may trail the newest release
scoop bucket add yazses https://github.com/MSKazemi/yazses; scoop install yazses
choco install yazses                            # administrator PowerShell
# Installer (.exe) — unsigned developer preview: https://github.com/MSKazemi/yazses/releases/latest
pipx install yazses                             # Python ≥ 3.11

Documentation

mskazemi.com/yazses is the full, searchable documentation site: install guides, the complete CLI and configuration reference, the feature catalog, architecture and troubleshooting.

Man page: the Debian package installs one, so man yazses works after an APT or .deb install. In a source checkout, read it with man -l man/yazses.1 (regenerate it with make man). pipx, pip and Snap installs do not put man pages on the system path; use yazses --help there.

Contributing

Contributions of every kind are welcome: bug reports, documentation, translations, packaging and code.

There is nothing to sign. No CLA, no DCO, no sign-off line, no bot to authorise, and no account beyond GitHub. Opening the pull request is the whole contract; section 5 of the Apache 2.0 licence already covers the licence grant.

Ways to start

• 🚀 First time? Start here. Pick the row that matches what you have in front of you and finish in 15–45 minutes.
• 🎯 Want the full list? Filter the open tasks by what you have (a browser, a terminal, a specific app or unusual hardware), how much time you have, and whether you want to write code. Each task names the files you may touch, the command that says you are done, and an honest time estimate.
• ⏱️ Fifteen minutes and no Python? Browser-only tasks can be done entirely in the GitHub web editor, with no clone and no install. Several are open to many contributors at once: translate the README (the introduction and Quick Start alone make a complete PR), add your microphone, share a config for your app or editor, or add your setup to SHOWCASE.md.
• 🐞 Found a bug or have an idea? Open an issue (the output of yazses doctor resolves most reports on its own) or ask in Discussions.

AI coding tools are optional, and you never need to pay for one. If you use one, read the safe agent guide first, and do not assume YazSes authorises or reimburses its costs. Using Google Jules? Connect Jules to your fork; no upstream collaborator access is needed, and direct upstream Jules remains gated by #447.

Development setup

YazSes is a Python 3.11+ project managed with uv:

git clone https://github.com/MSKazemi/yazses
cd yazses
uv sync
uv run python -m pytest tests/ -v
bash scripts/install-local.sh        # install locally + run as a user service

Before you open a pull request, run the same gates as CI (see CONTRIBUTING.md):

uv run python -m pytest tests/   # tests — must be green
uv run ruff check src tests scripts paper/benchmark   # lint — must be green
uv run mypy src                  # types — advisory (currently clean; don't add errors)

make check runs the tests, lint and the hygiene check in one step. Everything is fully offline: no microphone, model download or optional extras are needed. The suite is large, so a full run takes minutes rather than seconds; that is normal, not a hang. While you work, narrow it with uv run python -m pytest tests/test_foo.py or -k pattern.

No local setup? The repository ships a Dev Container, so opening it in GitHub Codespaces gives you a ready environment in the browser. Documentation, configuration, tests and pure-logic changes work fully there; anything that needs a real microphone, hotkey device or window focus needs a local machine.

Running unreleased code. To install your working tree as the system-wide yazses command (the Snap only ever carries a published release):

uv tool install --from . yazses --force   # (re)install the working tree as the `yazses` command
yazses restart                            # restart the daemon onto the new build
yazses --version                          # confirm the installed build

YazSes is offline-first. Please do not add network calls or telemetry.

Rust HCI exploration (archived)

This repository holds one product with two implementations: two generations of the same idea, not two apps. The one you install and run is the Python implementation on main. An early-stage Rust rewrite lives on the archive/rust-hci-v1 branch. Nothing here builds, installs or depends on it.

git checkout archive/rust-hci-v1
cargo build && cargo test --workspace   # optional backends: whisper, moonshine, llama-cpp, ollama, silero

Contributors

Thank you to everyone who has helped build YazSes ✨. Every bug report, documentation fix and patch counts. Contribution types follow the all-contributors emoji key (💻 code · 📖 docs · 🌍 translation · ⚠️ tests · 🛡️ security · 🚧 maintenance):

Mohsen Seyedkazemi Ardebili 🚧 💻 📖	lntutor 📖	HeaTTap 💻	jackie-cqz 💻	Parinitha-26 📖	AshSgDe29071999 💻 📖	Maqbool Ahmed 💻
Renji 💻 ⚠️ 📖 🛡️ 🚇	Sebastian Legarraga 💻 📓 📦	YossiMH 🤔 🐛 🔬	Prithvi4904 🌍	4nmus 🌍	hari 📖 💡	mercael 🚇 📖 ⚠️ 💡
Tanya Martin-McClellan 📓 🐛 📦	AtmanActive 🐛 📓	hoti-code 📓 🐛 📦	Jayavandhini M K 📖	Vishesh Patel 📖 📓 🐛	fall-water-zxc 📖 📓 🐛 📦 💡	Magnus Olsen 🐛 🤔
Aayaann Kausar 📖 📓	Aurora 💻 ⚠️ 📦 🔬	Elkero 📖 🌍 🐛	Guruharishb 🌍	DeliberateEnsemble 💻	doeil1614-ops 🌍	Musab Yusuf Üstün 🌍
sameer 📖	Harsh Raj Singhania 📖	Laura Saldarriaga Higuita 🌍	Tiyatrotist 📖	Amoth issac raj 📖	Adharsh Narayan 📖	LE-VAI 🤔 🔬
yangjie-AE 🌍	Vatsal Raina 💡	sahanaekin7-crypto 🌍	MarekMnahoncak 💻 ⚠️ 🚇	mrCabez 🌍	Vanam Shashi Haran Ram 🌍	filip-dzivy 🚇 ⚠️

Want to be on this list? Pick a good first issue; your first merged pull request adds you.

Citation

YazSes is described in a preprint. If it is useful in your research or projects, please cite:

Seyedkazemi Ardebili, M. (2026). YazSes: An Offline, Privacy-First, Cross-Platform Hold-to-Talk Voice-Dictation System. arXiv:2607.28878. https://arxiv.org/abs/2607.28878

@article{seyedkazemi2026yazses,
  title   = {YazSes: An Offline, Privacy-First, Cross-Platform Hold-to-Talk Voice-Dictation System},
  author  = {Seyedkazemi Ardebili, Mohsen},
  journal = {arXiv preprint arXiv:2607.28878},
  year    = {2026},
  url     = {https://arxiv.org/abs/2607.28878}
}

See CITATION.cff for machine-readable metadata (CFF 1.2.0).

Code signing policy

Windows builds are not code-signed yet. YazSes has applied to the SignPath Foundation free programme for open-source projects and is awaiting approval. The code signing policy on the website covers what gets signed, team roles, who approves each signing request and privacy, and explains how to verify a download today.

License

Apache 2.0. See LICENSE.

If YazSes is useful to you, a ⭐ on GitHub or a mention in your project, blog or talk is the best way to support its development.

Legal notice and responsible use

The materials in this repository are made available without warranties to the extent permitted by applicable law. Please read the Disclaimer and Responsible-Use Notice before relying on or deploying them. This notice does not change any existing software license or limit rights that cannot legally be waived.