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...
Fuente del modelo
- Tipo
- Other
- Tamaño del archivo
- 360 MB
- Modelo base
- swechatelangana/swecha-gonthuka-asr
- Versión
- vRevision 3b713c7
- Actualizado
- 26 oct 2026
- Descargas
- 6
- Fuente
- Hugging Face
Descripción de la fuente
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
Fuentes
1 fuente
Fuentes
1 fuenteVerificado 26 oct
Artefactos del modelo
1 artefacto
Artefactos del modelo
1 artefactoExtractos de fuentes
3 extractos
Extractos de fuentes
3 extractos--- 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
