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Pravalika2711/gonthuka-asr-finetuned
gonthuka-asr-finetuned is a automatic speech recognition model from Pravalika2711. Use it when you need speech turned into text. It is set up for transformers. The card lists the license as apache-2.0.
This repository contains a fine-tuned Automatic Speech Recognition (ASR) model for the Telugu language.
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From the Hugging Face model README
This repository contains a fine-tuned Automatic Speech Recognition (ASR) model for the Telugu language.
The model is based on Swecha Gonthuka ASR and has been fine-tuned using a custom Telugu speech dataset.
The model is capable of converting spoken Telugu audio into Telugu text and can be used for speech transcription and related ASR applications.
A custom Telugu speech dataset was used for fine-tuning.
Dataset details:
The dataset contains natural Telugu speech with manually verified transcripts.
| Parameter | Value |
|---|---|
| Base Model | swechatelangana/swecha-gonthuka-asr |
| Epochs | 10 |
| Learning Rate | 1e-5 |
| Batch Size | 4 |
| Gradient Accumulation | 2 |
| Optimizer | AdamW |
| Framework | Hugging Face Transformers |
| GPU | NVIDIA Tesla T4 |
The model was evaluated using Character Error Rate (CER).
| Metric | Value |
|---|---|
| CER | 0.14 |
| Character Accuracy | 86% |
Character Accuracy = (1 − CER) × 100
Install dependencies
pip install transformers torch librosa
Load the model
from transformers import pipeline
pipe = pipeline(
"automatic-speech-recognition",
model="Pravalika2711/gonthuka-asr-finetuned",
feature_extractor="Pravalika2711/gonthuka-asr-finetuned",
tokenizer="Pravalika2711/gonthuka-asr-finetuned"
)
Run inference
result = pipe("audio.wav")
print(result["text"])
This work is built upon the excellent Swecha Gonthuka ASR model.
Base Model:
https://huggingface.co/swechatelangana/swecha-gonthuka-asr
If you use this model, please cite both the original Swecha Gonthuka ASR model and this fine-tuned model.
@misc{gonthuka_finetuned,
title={Fine-Tuned Telugu ASR using Swecha Gonthuka ASR},
author={Pravalika Moraboyina},
year={2026},
publisher={Hugging Face}
}