metadata
license: cc-by-4.0
language:
- pa
base_model:
- parthiv11/stt_hi_conformer_ctc_large_v2
tags:
- speech_recognition
- entity_tagging
- dialect_prediction
- gender
- age
- intent
This speech tagger performs transcription for Punjabi, annotates key entities, predict speaker age, dialiect and intent.
Model is suitable for voiceAI applications, real-time and offline.
Model Details
- Model type: NeMo ASR
- Architecture: Conformer CTC
- Language: Punjabi
- Training data: AI4Bharat IndicVoices Punjabi V1 and V2 dataset
- Performance metrics: [Metrics]
Usage
To use this model, you need to install the NeMo library:
pip install nemo_toolkit
How to run
import nemo.collections.asr as nemo_asr
# Step 1: Load the ASR model from Hugging Face
model_name = 'WhissleAI/stt_pa_conformer_ctc_entities_age_dialiect_intent'
asr_model = nemo_asr.models.EncDecCTCModel.from_pretrained(model_name)
# Step 2: Provide the path to your audio file
audio_file_path = '/path/to/your/audio_file.wav'
# Step 3: Transcribe the audio
transcription = asr_model.transcribe(paths2audio_files=[audio_file_path])
print(f'Transcription: {transcription[0]}')
Dataset is from AI4Bharat IndicVoices Hindi V1 and V2 dataset.