Indic Tiny TTS: Hindi

Indic Tiny TTS: Hindi

Reads Hindi text in Devanagari script aloud with a female or a male voice, small enough to run on a CPU without a GPU. Made for developers adding Hindi speech to apps.

Made by sulabhkatiyar on Hugging Face. These notes are Mindket's, written from its model page and model card; the model's own files and license are on Hugging Face.

About

What it is: Indic Tiny TTS: Hindi is a small text-to-speech model for Hindi. It reads Devanagari script in either a female or a male voice and has 22.5 million parameters. It runs with PyTorch or ONNX Runtime and needs no GPU.

Who it suits: It suits developers who want Hindi speech on ordinary hardware, and researchers who compare small speech models by error rate.

Industry | Who uses it | How they use it | Example
Software | App developers | Read Hindi text aloud on devices without a GPU | Speaking a news sentence inside an app
Media | Content creators | Voice Hindi narration in a female or a male voice | Recording narration for a short video
Education | Language learning builders | Add spoken Hindi to lessons | Playing practice sentences to a learner
Research | Speech researchers | Compare small models by character error rate | Reading the card's benchmark tables

You can skip it if you need any language other than Hindi, since the model speaks Hindi only.

Where to use it:

• Python, with PyTorch or ONNX Runtime
• CPU-only machines, including an Apple M1 laptop and an x86 CPU
• An NVIDIA T4 GPU, which the card also measures
• Windows, macOS or Linux, once the files are downloaded

Use case | Who | What they get back
Hindi voice over | Creators | Spoken audio from Hindi text in one of two voices
App speech output | Developers | Fast speech on a CPU without a GPU
Model comparison | Researchers | Error rates against other open Hindi models

How to set it up:

• Python, to run the Hugging Face download tool
• The huggingface_hub package
• PyTorch or ONNX Runtime, to run the model

1. Install the Hugging Face hub package.
2. Download the model files to your computer.
3. Run the model with PyTorch or ONNX Runtime, following the full card.

pip install -U huggingface_hub
hf download sulabhkatiyar/indic-tiny-tts-hindi

How to use it: You give the model Hindi text written in Devanagari script and choose the female or the male voice. The part of the card shown here has no run command, so follow the run steps in the full card.

Tool | What it does
hf download | Fetches the model files to your computer
PyTorch | Runs the model, on a CPU or a GPU
ONNX Runtime | Another way to run the model on a CPU

Example: You pass one Hindi news sentence in Devanagari script and pick the male voice. The model returns spoken audio of that sentence, and on a single Apple M1 CPU thread it speaks about 38 times faster than real time.

For newcomers and experts: If you are new, download the files with the two commands above and open the card's Listen section to hear its samples. Then try one short Hindi sentence of your own.

If you know the field, it was trained on the 8-hour-per-voice Hindi subset of AI4Bharat Rasa at 24 kHz. The card measures character error rate on news sentences and held-out sentences. The trade-off is one language and two voices.

You give Hindi text in Devanagari script
You choose the female or the male voice
The model synthesizes the speech
You get audio back

Good to know:

Title: Character error rate on news sentences, lower is better
This model: 1.64%
Kokoro: 1.56%
Indic Parler TTS: 2.23%
Coqui XTTS: 2.37%
MMS Hindi: 3.83%
SYSPIN VITS Hindi: 5.58%

Title: Speed, times faster than real time
Apple M1 CPU, 1 thread: 38 x real time
Intel Xeon CPU, 1 thread: 7 x real time
NVIDIA T4 GPU: 62 x real time

• Languages: Hindi only, with one female and one male voice
• Collection: one of 12 tiny open models for 11 Indian languages and Indian English
• Training data: 8 hours per voice of Hindi female and male speech from AI4Bharat Rasa
• License: CC BY 4.0
• Cost to run: none named, and no GPU is needed
• Data it reaches: the Hindi text you give it, the audio it makes, and the files you download from Hugging Face
• Not for: languages other than Hindi

On Hugging Face, 13 November 2026

• Task: text to speech
• Parameters: 8.9M
• Weights: about 36 MB in F32; about 4 MB at 4-bit (estimate)
• Formats: Safetensors
• Downloads in the last 30 days: 508
• Likes: 2
• License: cc-by-4.0
• Languages: hi
• Tags: onnx, safetensors, text-to-speech, hindi, speech-synthesis, on-device

Links

• Model: https://huggingface.co/sulabhkatiyar/indic-tiny-tts-hindi
• Files: https://huggingface.co/sulabhkatiyar/indic-tiny-tts-hindi/tree/main

Get the model

Download its files with Hugging Face's command line:

pip install -U huggingface_hub
hf download sulabhkatiyar/indic-tiny-tts-hindi

Then follow the usage in its model card. Nothing in this kit runs by itself.