deekshitha1206/swecha-gonthuka-rayalaseema-dialect

Swecha Gonthuka Rayalaseema Telugu ASR Model

Model Description

This model is a fine-tuned Automatic Speech Recognition (ASR) model developed for recognizing the Rayalaseema dialect of Telugu. It is based on the Wav2Vec2 architecture and fine-tuned on Telugu speech collected through the Swecha Gonthuka initiative.

Model Details

• Task: Automatic Speech Recognition (ASR)
• Architecture: Wav2Vec2
• Framework: Hugging Face Transformers
• Language: Telugu (te)
• Dialect: Rayalaseema
• Base Model: swechatelangana/swecha-gonthuka-asr

Intended Use

This model is intended for:

• Telugu speech transcription
• Rayalaseema dialect recognition
• Speech dataset research
• Educational and accessibility applications

Training Data

The model was fine-tuned using Telugu speech recordings collected from native speakers of the Rayalaseema dialect.

Evaluation

The model was evaluated using Word Error Rate (WER). Performance depends on audio quality and speaker characteristics.

Limitations

• Designed primarily for Rayalaseema Telugu.
• Performance may decrease for other Telugu dialects.
• Background noise can reduce transcription accuracy.

Citation

If you use this model in your work, please cite the Swecha Gonthuka project.

License

Apache License 2.0