| --- |
| language: |
| - fa |
| license: mit |
| pipeline_tag: text-to-speech |
| base_model: Reza2kn/Gooya-RizehPizeh-v1.5 |
| library_name: piper |
| model_type: text-to-speech |
| tags: |
| - audio |
| - text-to-speech |
| - piper |
| - vits |
| - persian |
| - farsi |
| - negara |
| pretty_name: Gooya RizehPizeh v2 |
| --- |
| |
| # Gooya RizehPizeh v2 |
|
|
| Persian single-speaker Piper/VITS2 voice trained on full, unchunked Wikipedia recordings whose audio/transcript agreement passed AvaSanj. It uses a case-sensitive Negara-style phonetic/Finglish frontend and produces 22,050 Hz mono audio. |
|
|
| ## Current release |
|
|
| This revision replaces the earlier segmented-data v2 model with the user-selected unchunked/AvaSanj-approved 50K run. |
|
|
| - Full checkpoint: `checkpoint/gooya-rizehpizeh-v2-unchunked-avasanj-step50000-val_mel0.4138.ckpt` |
| - Checkpoint SHA-256: `8b52b3b6060b4698aba0c8bbd2f9b338aa6ba811d28a620e5f492c0fa1ae4d2b` |
| - Piper/browser model: `gooya-rizehpizeh-v2.onnx` |
| - ONNX SHA-256: `3f85f450fc21415e1eddaa0aa894c667e76d14aa9a342c4e77f1f9009b96f170` |
| - ONNX config SHA-256: `981770210ac1aea618cb8134597127911051deabf9900824df3388f209a884fa` |
| - Generator parameters: approximately 23.7M |
| - Sample rate: 22,050 Hz |
| - Speakers: 1 |
| - Phoneme type: `text` |
| - Symbol inventory: 256 IDs |
|
|
| ## Training data |
|
|
| The parent corpus comes from the approved Persian rows in [`Reza2kn/Wikipedia-FA-EN-DeepSeek-V4-Flash-0731`](https://huggingface.co/datasets/Reza2kn/Wikipedia-FA-EN-DeepSeek-V4-Flash-0731). |
|
|
| - Train: 1,290 full recordings, 21.1455 hours |
| - Parent-disjoint validation: 100 full recordings, 1.6445 hours |
| - Untouched sealed-eval agreement slice: 253 recordings, 4.1080 hours |
| - Recording duration: 38.68–95.96 seconds; mean 58.94 seconds |
| - Phoneme IDs per recording: 1,711–3,423; mean 2,174.65 |
| - AvaSanj compact CER threshold: `<= 0.12` |
| - Train/validation/sealed-eval parent overlap: zero |
| - Audio transform: none |
| - Silence trimming: disabled |
| - Segmentation/chunking: none |
|
|
| The 253-row sealed-eval agreement slice was not consumed by training or checkpoint selection. The complete selection and hash receipt is in `training/unchunked-avasanj-agree-report.json`. |
|
|
| ## Lineage and training |
|
|
| The original v1.5 production ONNX had no matching resumable checkpoint. Its 350 inference-time generator tensors were reconstructed into a compatible trainable Piper checkpoint; training-only branches absent from the ONNX came from the compatible Mana template. Recovery receipts remain under `training/`. |
|
|
| The promoted run resumed from that recovered v1.5 state and used: |
|
|
| - BF16 mixed precision |
| - Batch size 1 |
| - Generator learning rate `5e-6` |
| - Discriminator learning rate `2.5e-6` |
| - Configured limit: 50,000 optimizer steps |
| - Final/best validation mel: `0.4138` |
|
|
| The exact continuation script is `training/train_unchunked_avasanj_agree_full50k.sh`. |
|
|
| ## Validation |
|
|
| The published ONNX is self-contained and has no external tensor file. Direct ONNX Runtime CPU inference passed on both the canonical and long colloquial probes with finite, positive-length output. The same WAVs used for human listening are included under `samples/`. |
|
|
| - Inputs: `input`, `input_lengths`, `scales` |
| - Output: `output` |
| - File size: 63,516,051 bytes |
| - Canonical sample: 4.7137 seconds |
| - Long colloquial sample: 12.6084 seconds |
|
|
| Machine-readable receipts are under `browser/` and `training/`. |
|
|
| ## Inference |
|
|
| Input must already be case-sensitive Negara-compatible phonetic text: |
|
|
| ```bash |
| echo "zurxAneye vahdat yek makAne varzeSi dar Sahre borujerd ast." | \ |
| piper --model gooya-rizehpizeh-v2.onnx \ |
| --config gooya-rizehpizeh-v2.onnx.json \ |
| --output_file output.wav |
| ``` |
|
|
| For long-form narration, split at semantic sentence or clause boundaries into substantial spans and join them with boundary-aware pauses. Tiny fixed chunks tend to sound breathy and robotic. |
|
|
| ## Limitations |
|
|
| - G2P/Finglish quality remains the dominant source of pronunciation errors. |
| - The approved training labels are flat Negara phoneme sequences; existing internal punctuation was not available in those labels. |
| - Very long single-pass phoneme sequences can still collapse or omit content; use substantial semantic spans. |
| - Proper nouns may require corrected phonetic input. |
|
|
| ## License |
|
|
| MIT. See `LICENSE`. |
|
|
