Whisper Small Bengali

This is a fine-tuned Whisper Small model for Bengali (Bangla) speech recognition.

Model Details

• Base Model: openai/whisper-small
• Language: Bengali (bn)
• Training Steps: 2000
• Final Training Loss: N/A

Usage

from transformers import WhisperProcessor, WhisperForConditionalGeneration, WhisperTokenizer
import torch
import librosa

# Load model and tokenizer
model = WhisperForConditionalGeneration.from_pretrained("Noobbbbb/whisper-small-bn")
tokenizer = WhisperTokenizer.from_pretrained("Noobbbbb/whisper-small-bn")
processor = WhisperProcessor.from_pretrained("Noobbbbb/whisper-small-bn")

# Load audio (must be 16kHz)
audio, sr = librosa.load("audio.wav", sr=16000)

# Extract features
input_features = processor.feature_extractor(
    audio, 
    sampling_rate=16000, 
    return_tensors="pt"
).input_features

# Generate transcription
with torch.no_grad():
    generated_ids = model.generate(input_features, max_length=448)
    
# Decode
transcription = tokenizer.decode(generated_ids[0], skip_special_tokens=True)
print(transcription)

Training Details

• Training Data: openslr37
• Language: Bengali (bn)
• Training Steps: 2000
• Batch Size: 4
• Learning Rate: 1e-05
• Optimizer: AdamW
• eval_wer: 0.3080158337456705

Limitations

• Optimized for Bengali speech only
• Works best with clear audio at 16kHz sampling rate
• May not perform well on heavily accented or noisy audio

Acknowledgments

Based on OpenAI's Whisper model: https://github.com/openai/whisper