Ideal Binary Mask

import nussl
import matplotlib.pyplot as plt
import time

start_time = time.time()

def visualize_and_embed(sources):
    plt.figure(figsize=(10, 6))
    plt.subplot(211)
    nussl.utils.visualize_sources_as_masks(sources,
        y_axis='mel', db_cutoff=-40, alpha_amount=2.0)
    plt.subplot(212)
    nussl.utils.visualize_sources_as_waveform(
        sources, show_legend=False)
    plt.show()
    nussl.play_utils.multitrack(sources)

musdb = nussl.datasets.MUSDB18(
    download=True, sample_rate=16000,
    strict_sample_rate = False
)
i = 39
item = musdb[i]
mix = item['mix']
source_names = sorted(list(item['sources'].keys()))
sources = [item['sources'][k] for k in source_names]

separator = nussl.separation.benchmark.IdealBinaryMask(
    mix, sources)
estimates = separator()
estimates = {
    source_names[i]: e for i, e in enumerate(estimates)
}
visualize_and_embed(estimates)

end_time = time.time()
time_taken = end_time - start_time
print(f'Time taken: {time_taken:.4f} seconds')

Time taken: 27.2733 seconds