echo 'Hej, hur mår du idag?' | piper \
  --model sv_SE-alma-medium.onnx \
  --config sv_SE-alma-medium.onnx.json \
  --output_file output.wav \
  --noise-scale 0.8 --noise-w 0.6 --length-scale 0.9

With GNOME Spiel & Orca (accessibility)

Alma integrates with libspiel — GNOME's modern speech framework — via speech-provider-piper.

Architecture:

Orca (screen reader)
  └─ libspiel (GObject Introspection client library)
       └─ D-Bus → ai.piper.Speech.Provider (speech-provider-piper)
            └─ Piper VITS engine + ONNX model
                 └─ Voice files in /usr/share/piper-voices/

libspiel replaces the aging speech-dispatcher with a modern D-Bus-based approach:

Each voice is an independent D-Bus service — auto-activated on demand
No central daemon needed
Hot-swappable voices without restarting
GStreamer pipeline for audio output
Full GObject Introspection bindings (Python, JS, Vala, etc.)

Install everything from our PPA:

bash

# Add repository
wget -qO- https://yeager.github.io/debian-repo/yeager-repo-key.asc | \
  sudo tee /usr/share/keyrings/yeager-repo.asc > /dev/null
sudo tee /etc/apt/sources.list.d/yeager.sources << SOURCES
Types: deb
URIs: https://yeager.github.io/debian-repo/
Suites: stable
Components: main
Signed-By: /usr/share/keyrings/yeager-repo.asc
SOURCES

sudo apt update

# Install speech stack + Alma voice
sudo apt install libspiel-1.0-0 speech-provider-piper piper-voice-sv-alma

# Optional: development headers and GObject Introspection
sudo apt install libspiel-dev gir1.2-spiel-1.0

Test with spiel CLI:

spiel speak "Hej! Det här är Alma, en svensk röst."

Available packages:

Package	Description
`libspiel-1.0-0`	Spiel client library
`libspiel-dev`	Development headers
`gir1.2-spiel-1.0`	GObject Introspection bindings
`speech-provider-piper`	Piper D-Bus speech provider (Rust)
`piper-voice-sv-alma`	This voice model
`libpiper`	Piper phonemize library

Download

DEB package: sudo apt install piper-voice-sv-alma (PPA)
GitHub Release: v1.0.0-alma
Direct download: sv_SE-alma-medium.onnx (61 MB)

Training Details

Base model: sv_SE-alma-medium (Piper VITS)
Dataset: NST Swedish TTS Dataset (CC BY 4.0)
Samples: 1,875 audio clips
Epochs: 10,000 (checkpoints every 100)
GPU: NVIDIA RTX 4080
Precision: 32-bit
Real-time factor: ~0.025x (40× faster than real-time)

License

CC BY 4.0 (same as training data)

yeagersthlm/piper-voice-sv-alma

Alma — Swedish Piper TTS Voice (medium)

Quality: 8/10

Listen

Optimized Inference Parameters

Usage

Standalone Piper

With GNOME Spiel & Orca (accessibility)

Download

Training Details

Links

License

yeagersthlm/
piper-voice-sv-alma