| # Piper TTS Training Script for Saudi Arabic (MSA) | |
| # This script trains a Piper voice model using the prepared training data | |
| cd /root/piper_msa/piper1-gpl | |
| # Activate virtual environment | |
| source .venv/bin/activate | |
| # Set PyTorch memory optimization | |
| export PYTORCH_CUDA_ALLOC_CONF=expandable_segments:True | |
| # Training command - optimized for GPU memory | |
| # Reduced batch size from 32 to 8 to avoid OOM errors | |
| python3 -m piper.train fit \ | |
| --data.voice_name "saudi_msa" \ | |
| --data.csv_path /root/piper_msa/training_data.csv \ | |
| --data.audio_dir /root/piper_msa/raw_audio/ \ | |
| --model.sample_rate 22050 \ | |
| --data.espeak_voice "ar" \ | |
| --data.cache_dir /root/piper_msa/cache/ \ | |
| --data.config_path /root/piper_msa/output/config.json \ | |
| --data.batch_size 8 | |
| echo "Training completed!" | |