Jatin K MalikandGitHub
008fd3138e
* fix(injection): use Ctrl+Shift+V when pasting into terminals Clipboard injection always sent Ctrl+V, which most terminal emulators ignore. Detect standalone terminal windows and send Ctrl+Shift+V, with a Settings override for nested IDE panels that window-class detection cannot see. * fix(injection): fail closed when terminal window probe is mocked Clipboard tests patch text_injector.subprocess.run, which replaces stdlib subprocess.run. Window detection now ignores non-string probe output so injection still uses Ctrl+V instead of raising TypeError. * docs: fix overclaimed terminal auto-detect in USER_GUIDE Auto-detect only runs on X11 and on Hyprland, Sway, and niri. GNOME and KDE Wayland stay on Ctrl+V unless you set Clipboard Paste Shortcut to Ctrl+Shift+V.
211 lines
10 KiB
Markdown
211 lines
10 KiB
Markdown
# User Guide
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This guide explains how to use Vocalinux effectively.
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## Getting Started
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After installing Vocalinux (see the [Installation Guide](INSTALL.md)), you can start the application from the terminal and optionally enable start-on-login.
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## Start on Login (Autostart)
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Vocalinux supports login autostart using the standard Linux desktop-session mechanism.
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- **Where to enable it**:
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- First-run welcome dialog
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- Tray menu: **Start on Login**
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- Settings dialog: **Start on Login**
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- **What Vocalinux creates**:
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- `vocalinux.desktop` in `$XDG_CONFIG_HOME/autostart/` or `~/.config/autostart/`
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- **How it starts**:
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- As a regular user GUI app in your desktop session (`--start-minimized`)
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- **What it does not do**:
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- It does not create a `systemd` service/unit for autostart
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### Desktop Compatibility Notes
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- Works on most mainstream desktop environments (GNOME, KDE, Xfce, Cinnamon, MATE, LXQt)
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- On minimal/custom window managers, autostart may require an autostart manager or desktop-specific startup hook
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## Basic Usage
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### Starting and Stopping Voice Typing
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1. **Launch the application**: Run `vocalinux` in a terminal or launch it from your application menu
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2. **Find the tray icon**: Look for the microphone icon in your system tray
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3. **Start voice typing**: Hold Right Alt (Option) by default, or use the tray menu / your configured shortcut
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4. **Speak clearly**: As you speak, your words will be transcribed into the currently focused application
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5. **Stop voice typing**: Release the key in push-to-talk (default), double-tap again in toggle mode, or use the tray menu
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### Dictation formatting
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Vocalinux capitalizes the start of dictation and letters after `.`, `!`, or `?`. Each completed utterance also leaves a trailing space so the next push-to-talk or toggle session does not glue onto the previous sentence (`Hello.This` → `Hello. This`).
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### Dictating into terminals
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When Vocalinux injects through the clipboard (the usual Wayland / ydotool path), it sends **Ctrl+V** in ordinary text fields and **Ctrl+Shift+V** in terminal emulator windows. Auto-detect works on X11 and on Hyprland, Sway, and niri. On GNOME or KDE Wayland, set **Settings → Dictation → Clipboard Paste Shortcut** to **Ctrl+Shift+V**.
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Nested terminal panels inside an IDE are often invisible to window-class detection. If paste lands as a literal `^V` or does nothing, open **Settings → Dictation → Clipboard Paste Shortcut** and choose **Ctrl+Shift+V**. Choose **Ctrl+V** if a window was mis-detected as a terminal.
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### Understanding the Status Icons
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- **Microphone off** (gray): Voice typing is inactive
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- **Microphone on** (blue): Voice typing is active and listening
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- **Microphone processing** (orange): Voice typing is processing your speech
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## Voice Commands
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Vocalinux supports several commands that you can speak to control formatting:
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| Command | Action |
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|---------|--------|
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| "new line" or "new paragraph" | Inserts a line break |
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| "period" or "full stop" | Types a period (.) |
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| "comma" | Types a comma (,) |
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| "question mark" | Types a question mark (?) |
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| "exclamation point" or "exclamation mark" | Types an exclamation point (!) |
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| "semicolon" | Types a semicolon (;) |
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| "colon" | Types a colon (:) |
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| "delete that" or "scratch that" | Deletes the last sentence |
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| "capitalize" or "uppercase" | Capitalizes the next word |
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| "all caps" | Makes the next word ALL CAPS |
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## Tips for Better Recognition
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1. **Use a good microphone**: A quality microphone significantly improves recognition accuracy
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2. **Speak clearly**: Enunciate your words clearly but naturally
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3. **Moderate pace**: Don't speak too quickly or too slowly
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4. **Quiet environment**: Minimize background noise when possible
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5. **Learn commands**: Familiarize yourself with voice commands for punctuation and formatting
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6. **Use GPU acceleration**: If you have a GPU (AMD, Intel, or NVIDIA), whisper.cpp will automatically use it for faster transcription
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7. **Choose the right model**:
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- For real-time dictation: Use `tiny` or `base` (fastest)
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- For better accuracy: Use `small`, `medium`, or `large`
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- For English-only dictation: Choose an `.en` specialization
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- For lower-memory systems: Choose a quantized specialization such as `q5_0` or `q5_1`
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8. **Check debug logs**: Run `vocalinux --debug` to see which backend is being used (Vulkan, CUDA, or CPU)
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## Customization
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### Keyboard Shortcut
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Vocalinux supports two shortcut modes for controlling voice typing:
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- **Push-to-talk mode (default)**: Hold Right Alt (Option on Mac-layout keyboards) to speak, then release to stop
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- **Toggle mode**: Double-tap the configured shortcut key to start/stop voice typing
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- Configure mode and key in **Settings -> Shortcuts**
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### Model Settings
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You can change the speech recognition engine and model for better accuracy or faster performance:
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### Choosing Your Engine
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Vocalinux now offers **three speech recognition engines**:
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1. **whisper.cpp** ⭐ (Default) - High-performance C++ engine
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- Fastest installation (~1-2 min)
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- Works with AMD, Intel, NVIDIA GPUs via Vulkan
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- True multi-threading (no Python GIL)
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- Best for most users
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2. **Whisper** (OpenAI) - PyTorch-based engine
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- NVIDIA GPU only (requires CUDA)
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- Larger download (~2.3GB with PyTorch)
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- Installation takes ~5-10 min
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- Use if you specifically need PyTorch features
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3. **VOSK** - Lightweight engine
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- Smallest footprint (~40MB)
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- CPU only
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- Great for older systems or minimal resource usage
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### Changing Engine and Model
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1. Open settings from the tray icon menu (right-click)
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2. Open the **Speech Engine** page in the settings sidebar (search works if you prefer)
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3. Select your **Speech Engine**:
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- whisper_cpp (recommended)
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- whisper
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- vosk
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4. Select your **Model Size**:
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- **tiny** (~74MB) - Fastest, good for real-time dictation
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- **base** (~141MB) - Good balance
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- **small** (~465MB) - Better accuracy
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- **medium** (~1.5GB) - High accuracy
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- **large** (~3.0GB) - Best accuracy, slower
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5. For whisper.cpp, select a **Specialization**:
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- **Standard multilingual** - Best default for auto-detect or non-English dictation
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- **English-only** - Choose when you dictate only in English
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- **Quantized** - Lower memory and smaller downloads with a possible accuracy tradeoff
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- **Turbo** - Faster large-v3 option with strong accuracy
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- **Legacy large** - Use only if you specifically need an older large model version
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English-only whisper.cpp specializations limit the language selector to English.
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### Removing unused models
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Open Settings and go to **Speech Model**. If leftover files are on disk that are
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not the model currently selected, **Unused downloads** appears under the model
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info card. Expand it to delete leftovers one at a time. Confirming removes those
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files from `~/.local/share/vocalinux`. Vocalinux will download a model again if
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you select it later. Packaged system-wide VOSK models are left alone. The section
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is hidden when there is nothing unused to delete.
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### When to Use Each Model
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**For real-time dictation:** Use **tiny** or **base** - they're fast enough to keep up with your speech.
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**For transcription:** Use **small** or **medium** - better accuracy for recorded audio.
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**For maximum accuracy:** Use **large** - best results but requires more RAM and GPU power.
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**For lower-memory systems:** Use a quantized whisper.cpp specialization such as **Q5** or **Q8**.
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**For English-only dictation:** Use an **English-only** specialization and keep the language set to English.
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### GPU Acceleration
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**whisper.cpp** uses GPU acceleration when the bundled pywhispercpp libraries include Vulkan or CUDA:
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- **Vulkan** (AMD, Intel, NVIDIA) when `libggml-vulkan` is present
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- **CUDA** (NVIDIA) when `libggml-cuda` is present
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- **CPU** when those libraries are missing, even if Settings lists a GPU
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Host tools such as `vulkaninfo` only describe the machine. The engine follows the libraries actually loaded. Look for `GPU backend: vulkan` or `GPU backend: cuda` after the model loads. `CPU-only; pywhispercpp lacks GPU libraries` means inference is on the CPU.
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On multi-GPU machines, Vocalinux prefers a discrete Vulkan device when one is present and skips software renderers such as llvmpipe. Override the device under **Settings → Performance → Vulkan GPU**.
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Pip wheels of pywhispercpp are often CUDA builds. In that case Vocalinux always uses CUDA device 0 (the first NVIDIA GPU), because Vulkan GPU indices do not match CUDA ordinals. On a hybrid laptop the NVIDIA GPU is usually Vulkan GPU 1; feeding that index into CUDA would land on the CPU fallback instead.
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If you need a second NVIDIA GPU, either set `CUDA_VISIBLE_DEVICES` before starting Vocalinux or install a Vulkan-built pywhispercpp so the Performance GPU picker applies.
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`install.sh` rebuilds pywhispercpp with Vulkan or CUDA when it can. Prefer that launcher (or the wrapper it installs) so `LD_LIBRARY_PATH` includes the GPU libs. Raw `venv/bin` binaries can come up CPU-only.
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AppImages built from this tree compile pywhispercpp with Vulkan and use the host Vulkan driver at runtime. Older AppImages shipped the CPU-only wheel; if you see the `lacks GPU libraries` line, download a newer AppImage or use `install.sh`.
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Hybrid / PRIME / Optimus laptops: picking NVIDIA in Settings is enough when pywhispercpp is Vulkan-built. `prime-run` is not required for Vulkan, and it cannot fix a CPU-only wheel. Install `vulkan-tools` so `vulkaninfo` can enumerate devices; without it, whisper.cpp may default to GPU 0 (often the iGPU).
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To check which backend is being used, look for these log messages when starting Vocalinux (`vocalinux --debug`):
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```
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[INFO] whisper.cpp using Vulkan GPU backend: AMD Radeon RX 6800
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[INFO] Using Vulkan GPU [0]: AMD Radeon RX 6800
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[INFO] whisper.cpp configured with n_threads=4 (GPU backend: vulkan)
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```
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### Auto-pause and model keep-alive
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Optional power-saving controls live under settings:
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- **Auto-pause apps** — unload the speech model while configured apps/games are running, then reload when they exit
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- **Model keep-alive** — unload the model after a configurable idle timeout so idle dictation does not keep GPU/CPU resources warm
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## Troubleshooting
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If you encounter issues, check the [Installation Guide](INSTALL.md) troubleshooting section or run the application with debug logging:
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```bash
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vocalinux --debug
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```
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Check the logs for error messages and possible solutions.
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