Pravalika2711/gonthuka-asr-finetuned

Telugu ASR Fine-Tuned Model

Overview

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.

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Base Model

• Model: swechatelangana/swecha-gonthuka-asr
• Architecture: Wav2Vec2ForCTC
• Framework: Hugging Face Transformers
• Language: Telugu

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Fine-Tuning Dataset

A custom Telugu speech dataset was used for fine-tuning.

Dataset details:

• Approximately 752 Telugu audio recordings
• Audio Format: WAV
• Sampling Rate: 16 kHz
• Mono Audio
• Telugu Transcriptions

The dataset contains natural Telugu speech with manually verified transcripts.

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Training Configuration

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

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Evaluation

The model was evaluated using Character Error Rate (CER).

Metric	Value
CER	0.14
Character Accuracy	86%

Character Accuracy = (1 − CER) × 100

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Usage

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"])

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Applications

• Telugu Speech Recognition
• Voice Assistants
• Speech-to-Text Systems
• Accessibility Applications
• Telugu Language Research
• Educational Applications

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Limitations

• Performance may decrease for noisy environments.
• Works best with 16 kHz mono WAV audio.
• Accuracy depends on speaker accent and recording quality.

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Acknowledgements

This work is built upon the excellent Swecha Gonthuka ASR model.

Base Model:

https://huggingface.co/swechatelangana/swecha-gonthuka-asr

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Citation

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}
}