asteroid.metrics module¶
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asteroid.metrics.
get_metrics
(mix, clean, estimate, sample_rate=16000, metrics_list='all', average=True, compute_permutation=False)[source]¶ Get speech separation/enhancement metrics from mix/clean/estimate.
Parameters: - mix (np.array) – ‘Shape(D, N)’ or ‘Shape(N, )’.
- clean (np.array) – ‘Shape(K_source, N)’ or ‘Shape(N, )’.
- estimate (np.array) – ‘Shape(K_target, N)’ or ‘Shape(N, )’.
- sample_rate (int) – sampling rate of the audio clips.
- metrics_list (Union [str, list]) – List of metrics to compute. Defaults to ‘all’ ([‘si_sdr’, ‘sdr’, ‘sir’, ‘sar’, ‘stoi’, ‘pesq’]).
- average (bool) – Return dict([float]) if True, else dict([array]).
- compute_permutation (bool) – Whether to compute the permutation on estimate sources for the output metrics (default False)
Returns: dict –
- Dictionary with all requested metrics, with ‘input_’ prefix
for metrics at the input (mixture against clean), no prefix at the output (estimate against clean). Output format depends on average.
Examples
>>> import numpy as np >>> import pprint >>> from asteroid.metrics import get_metrics >>> mix = np.random.randn(1, 16000) >>> clean = np.random.randn(2, 16000) >>> est = np.random.randn(2, 16000) >>> metrics_dict = get_metrics(mix, clean, est, sample_rate=8000, >>> metrics_list='all') >>> pprint.pprint(metrics_dict) {'input_pesq': 1.924380898475647, 'input_sar': -11.67667585294225, 'input_sdr': -14.88667106190552, 'input_si_sdr': -52.43849784881705, 'input_sir': -0.10419427290163795, 'input_stoi': 0.015112115177091223, 'pesq': 1.7713886499404907, 'sar': -11.610963379923195, 'sdr': -14.527246041125844, 'si_sdr': -46.26557128489802, 'sir': 0.4799929272243427, 'stoi': 0.022023073540350643}