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Swecha Gonthuka Rayalaseema Dialect

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...

KindOtherBase modelswechatelangana/swecha-gonthuka-asrVersionRevision 3b713c7Bgrade

Model source

Kind
Other
File size
360 MB
Base model
swechatelangana/swecha-gonthuka-asr
Version
vRevision 3b713c7
Updated
Oct 26, 2026
Downloads
6
Source
Hugging Face

Source description

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

Sources

1 source
Hugging FacePrimaryVersion 3b713c702dd2f6893a57fa8bb0c533b2e4cdd4db
huggingface.co/deekshitha1206/swecha-gonthuka-rayalaseema-dialect/tree/3b713c702dd2f6893a57fa8bb0c533b2e4cdd4db

Verified Oct 26

Model artifacts

1 artifact

model.safetensors

safetensors · 360 MB · SHA-256 ba3083a1ae44…a1ea · Hugging Face

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Source excerpts

3 excerpts

--- language: - te license: apache-2.0 library_name: transformers pipeline_tag: automatic-speech-recognition base_model: swechatelangana/swecha-gonthuka-asr tags: - telugu - rayalaseema - automatic-speech-recognition - wav2vec2 - speech-recognition --- # 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

Source context: 6 downloads · 0 likes · Pipeline automatic-speech-recognition · Library transformers · Repo deekshitha1206/swecha-gonthuka-rayalaseema-dialect

Source context: 55 downloads · 0 likes · Pipeline automatic-speech-recognition · Library transformers · Repo deekshitha1206/swecha-gonthuka-rayalaseema-dialect