WhissleAI/speech-tagger_bn_ctc_meta

Bengali Speech Tagger - Conformer CTC Model

This speech tagger performs transcription for Bengali, annotates key entities, predicts speaker age, dialect and intent.

Model Details

• Model Type: NeMo ASR
• Architecture: Conformer CTC
• Language: Bengali
• Training Data: AI4Bharat IndicVoices Bengali V1 and V2 dataset
• Task: Speech Recognition with Entity Tagging

Usage

import nemo.collections.asr as nemo_asr

# Load model
asr_model = nemo_asr.models.EncDecCTCModel.from_pretrained('WhissleAI/speech-tagger_bn_ctc_meta')

# Transcribe audio
transcription = asr_model.transcribe(['path/to/audio.wav'])
print(transcription[0])

Model Training

• Base model: Conformer CTC
• Fine-tuned on AI4Bharat IndicVoices Marathi dataset
• Optimized for real-time transcription

License & Attribution

Please cite AI4Bharat when using this model: https://indicvoices.ai4bharat.org/