Swecha Gonthuka Finetuned

Swecha Gonthuka Fine-Tuned Telugu ASR

Overview

This repository contains a fine-tuned Automatic Speech Recognition (ASR) model for the Telugu language.

The model is built on Swecha Gonthuka ASR and further fine-tuned using a custom Telugu speech dataset to improve transcription quality and recognition accuracy for Telugu speech.

This model converts spoken Telugu audio into Telugu Unicode text and can be used in a wide range of speech recognition applications.

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Features

• 🎤 Telugu Automatic Speech Recognition (ASR)
• 📝 Speech-to-Text Conversion
• ⚡ Fine-tuned Wav2Vec2ForCTC Model
• 🤗 Compatible with Hugging Face Transformers
• 🎧 Supports 16 kHz WAV Audio
• 📚 Custom Telugu Speech Dataset Fine-tuning

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Model Details

Property	Value
Model Name	swecha-gonthuka-finetuned
Hugging Face Repository	Vasantha23/swecha-gonthuka-finetuned
Model Type	Wav2Vec2ForCTC
Framework	Hugging Face Transformers
Base Model	swechatelangana/swecha-gonthuka-asr
Language	Telugu
Task	Automatic Speech Recognition
Fine-tuned By	Vasantha

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Base Model

This model is fine-tuned from:

swechatelangana/swecha-gonthuka-asr

Model Lineage

Harveenchadha/wav2vec2-pretrained-clsril-23-10k
                ↓
swechatelangana/swecha-gonthuka-asr
                ↓
Vasantha23/swecha-gonthuka-finetuned

After Hugging Face processes the repository metadata, this lineage should automatically appear under the Model Tree section.

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Fine-Tuning Dataset

The model was fine-tuned using a custom Telugu speech dataset.

Dataset Characteristics

• Language: Telugu
• Audio Format: WAV
• Sampling Rate: 16 kHz
• Mono Audio
• UTF-8 Telugu Transcriptions
• Task: Automatic Speech Recognition

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Training Configuration

Hyperparameter	Value
Architecture	Wav2Vec2ForCTC
Framework	Hugging Face Transformers
Optimizer	AdamW
Learning Rate	1e-4
Batch Size	8
Epochs	10
Mixed Precision	FP16
Loss Function	CTC Loss

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Installation

pip install transformers torchaudio librosa soundfile

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Usage

Load Processor and Model

from transformers import AutoProcessor, AutoModelForCTC

processor = AutoProcessor.from_pretrained(
    "Vasantha23/swecha-gonthuka-finetuned"
)

model = AutoModelForCTC.from_pretrained(
    "Vasantha23/swecha-gonthuka-finetuned"
)

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Speech Recognition Pipeline

from transformers import pipeline

pipe = pipeline(
    "automatic-speech-recognition",
    model="Vasantha23/swecha-gonthuka-finetuned"
)

result = pipe("audio.wav")

print(result["text"])

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Manual Inference

import librosa
import torch
from transformers import AutoProcessor, AutoModelForCTC

processor = AutoProcessor.from_pretrained(
    "Vasantha23/swecha-gonthuka-finetuned"
)

model = AutoModelForCTC.from_pretrained(
    "Vasantha23/swecha-gonthuka-finetuned"
)

speech, sr = librosa.load("audio.wav", sr=16000)

inputs = processor(
    speech,
    sampling_rate=16000,
    return_tensors="pt",
    padding=True
)

with torch.no_grad():
    logits = model(inputs.input_values).logits

predicted_ids = torch.argmax(logits, dim=-1)

transcription = processor.batch_decode(predicted_ids)[0]

print(transcription)

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Example

Input

audio.wav

Output

ఈ రోజు వాతావరణం చాలా బాగుంది.

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Applications

This model can be used for:

• Telugu Speech Recognition
• Speech-to-Text Systems
• Voice Assistants
• Audio Transcription
• Subtitle Generation
• Educational Applications
• Research in Telugu ASR
• Accessibility Tools

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Performance

The model has been fine-tuned to improve Telugu speech recognition performance over the base model using a custom Telugu dataset.

Typical evaluation metrics include:

• Word Error Rate (WER)
• Character Error Rate (CER)

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Limitations

Performance may decrease in the following situations:

• Heavy background noise
• Low-quality recordings
• Multiple speakers
• Strong regional accents
• Very short audio clips

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Acknowledgements

This project builds upon the excellent work of:

• Swecha Telangana
• Hugging Face
• Hugging Face Transformers
• PyTorch
• Wav2Vec2
• Mozilla Common Voice Community

Special thanks to the creators of Swecha Gonthuka ASR for making the base Telugu ASR model publicly available.

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Citation

If you use this model in your work, please cite:

@misc{swecha_gonthuka_finetuned,
  title={Swecha Gonthuka Fine-Tuned Telugu ASR},
  author={Vasantha},
  year={2026},
  publisher={Hugging Face},
  url={https://huggingface.co/Vasantha23/swecha-gonthuka-finetuned}
}

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License

This model is released under the AGPL-3.0 License, consistent with the licensing of the base model.

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Contact

For questions, suggestions, or improvements, please open an issue in the Hugging Face repository or contact the repository maintainer.

Hugging Face Repository

https://huggingface.co/Vasantha23/swecha-gonthuka-finetuned