torch-stoi

import torch from torch import nn from torch_stoi import NegSTOILoss sample_rate = 16000 loss_func = NegSTOILoss(sample_rate=sample_rate) # Example dummy data clean_speech = torch.randn(2, sample_rate) # Batch of 2, 1 second audio noisy_speech = torch.randn(2, sample_rate) # Batch of 2, 1 second audio # In a real scenario, noisy_speech would be passed through a neural network # to produce an estimated clean speech signal. # For quickstart, let's assume `noisy_speech` is our `est_speech` for demonstration. est_speech = noisy_speech # Replace with your model's output # Compute loss loss_batch = loss_func(est_speech, clean_speech) print(f"Computed STOI loss: {loss_batch.mean().item()}")