vagdhenu

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. The base DiT + `vocab.txt` come from [`ai4bharat/IndicF5`](https://huggingface.co/ai4bharat/IndicF5) (auto-downloaded by the repo's setup). 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). 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. 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`. 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. 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).