Local Llama TTS

Synthesize speech locally using llama-tts and the OuteTTS-1.0-0.6B model.

Usage

You can use the wrapper script:

• scripts/tts-local.sh [options] "<text>"

Options

• -o, --output <file>: Output WAV file (default: output.wav)
• -s, --speaker <file>: Speaker reference file (optional)
• -t, --temp <value>: Temperature (default: 0.4)

Scripts

• Location: scripts/tts-local.sh (inside skill folder)
• Model: /data/public/machine-learning/models/text-to-speach/OuteTTS-1.0-0.6B-Q4_K_M.gguf
• Vocoder: /data/public/machine-learning/models/text-to-speach/WavTokenizer-Large-75-Q4_0.gguf
• GPU: Enabled via llama-tts.

Setup

1. Model: Download from OuteAI/OuteTTS-1.0-0.6B-GGUF
2. Vocoder: Download from ggml-org/WavTokenizer (Note: Felix uses a Q4_0 version, Q5_1 is linked here as a high-quality alternative).

Place files in /data/public/machine-learning/models/text-to-speach/ or update scripts/tts-local.sh.

Sampling Configuration

The model card recommends the following settings (hardcoded in the script):

• Temperature: 0.4
• Repetition Penalty: 1.1
• Repetition Range: 64
• Top-k: 40
• Top-p: 0.9
• Min-p: 0.05