Vagdhenu
Model weights for Vāgdhenu, a single-speaker Sanskrit chant (pārāyaṇa) TTS. MOS 4.6 (expert listener); conjuncts including retroflex aspirates render 100% correctly.
Fuente del modelo
- Tipo
- Other
- Tamaño del archivo
- 429 MB–1,26 GB
- Modelo base
- ai4bharat/IndicF5
- Versión
- vRevision d3d854b
- Actualizado
- 26 oct 2026
- Descargas
- 23
- Fuente
- Hugging Face
Descripción de la fuente
Vāgdhenu — Sanskrit Chant TTS (weights)
Model weights for Vāgdhenu, a single-speaker Sanskrit chant (pārāyaṇa) TTS. MOS ~4.6 (expert listener); conjuncts including retroflex aspirates render 100% correctly.
Files
| file | what |
|---|---|
voice_steer_ema_2026-06-17.pt | Production voice — voice-steered, more reference-responsive (the recommended default). |
voice_armA_ema_2026-06-11.pt | Fallback — reference-driven chant (voice + swara + pace from the reference clip). |
voc_bigvgan_EMA_2026-06-11.pth | Vocoder — NVIDIA BigVGAN-v2 fine-tuned on F5 vocos-mel (mandatory; vocos shivers on long vowels). |
The base DiT + vocab.txt come from ai4bharat/IndicF5 (auto-downloaded by the repo's setup).
Architecture
IndicF5 / F5-TTS — flow-matching DiT (OT-CFM mel-infilling, dim 1024 / depth 22 / heads 16, ~337M params, no native duration or pitch head) → BigVGAN-v2 vocoder. Sanskrit is routed through Kannada script (Devanagari triggers Hindi schwa-deletion).
Usage
See the GitHub repo — bash scripts/setup.sh downloads these weights to models/, then python src/render.py ... renders a Devanagari verse + meter to a chanted wav.
The key lever is the reference (F5 prosody is text-driven, not designable): supply the prosody you want as a clean, exactly-matched reference clip (the half-reference rule — ref_text must match the reference audio's spoken span on a word/daṇḍa boundary). A per-meter reference bank ships with the repo.
Training
Fine-tuned from IndicF5 on a ~5 h single-speaker Sanskrit chant corpus (prathoshap/vagdhenu-data); the production voice adds a voice-steering retrain on paired clips. Full method in the repo's docs/TECH_REPORT.md.
Intended use & limitations
Synthesis of classical Sanskrit chant (pārāyaṇa) for recitation, study, and accessibility. No Vedic svaras. Prosody is reference-driven, not arbitrarily designable. The voice is the author's own — please use responsibly and do not impersonate.
License & attribution
Our contribution under Apache-2.0. Built on AI4Bharat IndicF5 (MIT), NVIDIA BigVGAN-v2, and F5-TTS — the vocoder is a BigVGAN-v2 derivative; please observe NVIDIA's BigVGAN license terms. Cite Vāgdhenu (BibTeX with the technical report).
Fuentes
1 fuente
Fuentes
1 fuenteVerificado 26 oct
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Artefactos del modelo
3 artefactos
Artefactos del modelo
3 artefactosExtractos de fuentes
3 extractos
Extractos de fuentes
3 extractos--- language: - sa license: apache-2.0 pipeline_tag: text-to-speech base_model: ai4bharat/IndicF5 tags: - sanskrit - chant - text-to-speech - f5-tts - indicf5 - bigvgan --- # Vāgdhenu — Sanskrit Chant TTS (weights) Model weights for [**Vāgdhenu**](https://github.com/prathoshap/vagdhenu), a single-speaker Sanskrit **chant (pārāyaṇa) TTS**. MOS ~4.6 (expert listener); conjuncts including retroflex aspirates render 100% correctly. ## Files | file | what | |---|---| | `voice_steer_ema_2026-06-17.pt` | **Production voice** — voice-steered, more reference-responsive (the recommended default). | | `voice_armA_ema_2026-06-11.pt` | Fallback — reference-driven chant (voice + swara + pace from the reference clip). | | `voc_bigvgan_EMA_2026-06-11.pth` | **Vocoder** — NVIDIA BigVGAN-v2 fine-tuned on F5 vocos-mel (mandatory; vocos shivers on long vowels). | The base DiT + `vocab.txt` come from [`ai4bharat/IndicF5`](https://huggingface.co/ai4bharat/IndicF5) (auto-downloaded by the repo's setup). ## Architecture IndicF5 / F5-TTS — flow-matching **DiT** (OT-CFM mel-infilling, dim 1024 / depth 22 / heads 16, ~337M params, **no native duration or pitch head**) → BigVGAN-v2 vocoder. Sanskrit is routed through **Kannada script** (Devanagari triggers Hindi schwa-deletion). ## Usage See the [GitHub repo](https://github.com/prathoshap/vagdhenu) — `bash scripts/setup.sh` downloads these weights to `models/`, then `python src/render.py ...` renders a Devanagari verse + meter to a chanted wav. **The key lever is the reference** (F5 prosody is text-driven, not designable): supply the prosody you want as a clean, exactly-matched reference clip (the *half-reference rule* — `ref_text` must match the reference audio's spoken span on a word/daṇḍa boundary). A per-meter reference bank ships with the repo. ## Training Fine-tuned from IndicF5 on a ~5 h single-speaker Sanskrit chant corpus ([`prathoshap/vagdhenu-data`](https://huggingface.co/datasets/prathoshap/vagdhenu-data)); the production voice adds a voice-steering retrain on paired clips. Full method in the repo's `docs/TECH_REPORT.md`. ## Intended use & limitations Synthesis of classical Sanskrit chant (pārāyaṇa) for recitation, study, and accessibility. **No Vedic svaras.** Prosody is **reference-driven**, not arbitrarily designable. The voice is the author's own — please use responsibly and do not impersonate. ## License &...
Source context: 23 downloads · 0 likes · Pipeline text-to-speech · Library f5-tts · Repo leastgrey/vagdhenu
Source context: 28 downloads · 0 likes · Pipeline text-to-speech · Library f5-tts · Repo leastgrey/vagdhenu
