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Model: kenpath/svara-tts-v1 Source: Original Platform
2026-06-28 02:44:23 +08:00
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+---
+base_model: canopylabs/3b-hi-ft-research_release
+license: apache-2.0
+language:
+- hi   # Hindi
+- bn   # Bengali
+- mr   # Marathi
+- te   # Telugu
+- kn   # Kannada
+- bho  # Bhojpuri
+- mag  # Magahi
+- hne  # Chhattisgarhi
+- mai  # Maithili
+- as   # Assamese
+- brx  # Bodo
+- doi  # Dogri
+- gu   # Gujarati
+- ml   # Malayalam
+- pa   # Punjabi
+- ta   # Tamil
+- ne   # Nepali
+- sa   # Sanskrit
+- en   # English (Indian)
+tags:
+- text-to-speech
+- speech-synthesis
+- transformers
+- multilingual
+- indic
+- orpheus
+- lora
+- low-latency
+- gguf
+- zero-shot
+- emotions
+- discrete-audio-tokens
+task_categories:
+- text-to-speech
+pipeline_tag: text-to-speech
+pretty_name: Svara-TTS v1
+datasets:
+- SYSPIN
+- RASA
+- IndicTTS
+- SPICOR
+---
+
+# svara-TTS v1 — Open Multilingual TTS for India’s Voices
+
+[![🤗 Hugging Face - svara-tts-v1 Model](https://img.shields.io/badge/%F0%9F%A4%97%20Hugging%20Face-Model-black)](https://huggingface.co/kenpath/svara-tts-v1) 
+[![🤗 Hugging Face - Spaces](https://img.shields.io/badge/%F0%9F%A4%97%20Hugging%20Face-Spaces-green)](https://huggingface.co/spaces/kenpath/svara-tts)
+[![Open In Colab](https://colab.research.google.com/assets/colab-badge.svg)](https://colab.research.google.com/drive/15YxFo1DzdQNbFUIZ1HJA4AN4oHqKxGtg)
+[![GitHub](https://img.shields.io/badge/github-%23121011.svg?style=flat&logo=github&logoColor=white)](https://github.com/Kenpath/svara-tts-inference)
+
+**svara-TTS** is a developer-first multilingual TTS model for **19 languages** (18 Indic + Indian English).  
+Built on an Orpheus-style discrete audio token approach, it targets **clarity, expressiveness, and low-latency** on commodity GPUs/CPUs.  
+It supports light-weight **emotion/style control** (e.g., `<happy>`, `<sad>`, `<anger>`, `<fear>`) and simple **speaker identities** (`Language (Gender)`), with **zero-shot** adaptation paths.
+
+---
+
+## At a Glance
+
+- **Languages (19):** Hindi, Bengali, Marathi, Telugu, Kannada, Bhojpuri, Magahi, Chhattisgarhi, Maithili, Assamese, Bodo, Dogri, Gujarati, Malayalam, Punjabi, Tamil, Nepali, Sanskrit, Indian English.  
+- **Expressivity:** End-of-utterance style tags; natural prosody; code-switch aware.  
+- **Latency & Deployment:** Works well with **GGUF** exports; suitable for edge/CPU scenarios.  
+- **Adaptability:** **LoRA-friendly** for quick speaker/domain specialization.
+
+Try it live on the [**Demo Space**](https://huggingface.co/spaces/kenpath/svara-tts), or on **[Colab](https://colab.research.google.com/drive/15YxFo1DzdQNbFUIZ1HJA4AN4oHqKxGtg)**
+Deployment scripts and **inference repo** will be available soon. Watch our [Github](https://github.com/Kenpath/svara-tts-inference) for updates
+
+---
+
+## Prompting (Orpheus-style)
+
+- Place style/emotion tags **at the end** of the sentence:  
+  `आज... सच में अच्छी खबर है — शाम को मिलते हैं! <happy>`
+- Use punctuation to hint prosody (ellipses, commas, exclamation).
+- For technical or dense text, end with `<clear>` to prioritize intelligibility.
+
+> Speaker IDs follow a simple convention: **`Language (Gender)`** (e.g., `Marathi (Male)`).
+
+---
+
+## Training Data Summary
+
+Trained on **2000+ hours** of open, high-quality speech from **SYSPIN**, **RASA**, **IndicTTS**, and **SPICOR**, covering **~50 speakers** (balanced male/female) across **19 languages**.  
+Data was curated to encourage natural prosody, broad coverage, and stable multilingual transfer. See **Acknowledgments** for provenance.
+
+---
+
+## Intended Uses
+
+- Multilingual assistants, IVR, learning apps, reading aids, accessibility tools  
+- Content localization (education, public-information, civic services)  
+- Research on Indic prosody, emotion control, cross-lingual transfer
+
+## Out-of-Scope / Not Intended
+
+- Impersonation of private individuals or public figures without consent  
+- Deceptive content (fraud, harassment, misinformation)  
+- Safety-critical deployments without human oversight
+
+---
+
+## Limitations
+
+- **Proper nouns & rare entities:** may require spelling hints or `<clear>`.  
+- **Very long sentences:** chunk or add punctuation for natural prosody.  
+- **Emotion strength:** varies by language due to data density.  
+- **Code-mixing:** common patterns work; it’s not a deterministic rules engine.
+
+Many of these improve with targeted LoRA finetuning and better preprocessing.
+
+---
+
+## Responsible Use
+
+By using this model, you agree to follow applicable laws and ethical guidelines.  
+Avoid impersonation, harassment, targeted deception, or other harmful uses.  
+Where appropriate, disclose synthetic speech to end users.
+
+---
+
+## Sources & Links
+
+- **Model:** https://huggingface.co/kenpath/svara-tts-v1  
+- **Demo Space:** https://huggingface.co/spaces/kenpath/svara-tts  
+- **Inference repo:** https://github.com/Kenpath/svara-tts-inference  
+- **Colab:** https://colab.research.google.com/drive/15YxFo1DzdQNbFUIZ1HJA4AN4oHqKxGtg
+
+---
+
+## 🙏 Acknowledgments
+
+This work was developed by **[Kenpath Technologies](https://kenpath.ai/)** for the open-source community. We also thank RunPod for the startup credits that supported our GPU compute.
+
+- **Canopy Labs — Orpheus:** foundational ideas & open release  
+  Release: https://canopylabs.ai/releases/orpheus_can_speak_any_language  
+- **SPIRE Lab, IISc Bangalore** — **SYSPIN** (multilingual studio) and **SPICOR** (Indian English)  
+- **AI4Bharat** — **RASA** expressive speech  
+- **IIT Madras** — **IndicTTS**  
+- **Unsloth** — helpful notes & tooling  
+- **RunPod** — startup GPU credits that accelerated experiments
+
+---
+
+## License
+
+**Apache-2.0**
+
+---
+
+## Versioning & Changelog
+
+- **v1.0.0:** Initial public release (19 languages)