Self-contained experimental Persian text-to-speech: 9,451,575 parameters, including G2P, a contextual GrainSpeech acoustic model, and a tiny speaker-adapted HiFi-GAN vocoder. Produces 24 kHz mono WAV audio. The entire stack is included in this repository and runs offline after downloading and installing dependencies. This is the stack used for the September 24 listening comparison. It includes the full 8.07M Negara v7.1 model and its overlay. No Vocos, AvaSanj, training corpus, external checkpoint, Lightning, or remote inference service is required. Python 3.10+; CPU is the default. CUDA is optional. PyTorch is a separate runtime dependency: the model weight size is not the installation…
Open weights
apache-2.0
Self-contained experimental Persian text-to-speech: 2,221,495 parameters, including G2P, a contextual GrainSpeech acoustic model, and a tiny speaker-adapted HiFi-GAN vocoder. Produces 24 kHz mono WAV audio. The entire stack is included in this repository and runs offline after downloading and installing dependencies. This is the stack used for the September 24 listening comparison. It includes the newer broad-corpus 837K student selected at epoch 16, not the earlier Nasle-only student. No Vocos, AvaSanj, training corpus, external checkpoint, Lightning, or remote inference service is required. Python 3.10+; CPU is the default. CUDA is optional. PyTorch is a separate runtime dependency: the…
Open weights
apache-2.0
