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Gains are recorded; loudness is not equalized.","references":["https://docs.scipy.org/doc/scipy/reference/generated/scipy.signal.welch.html","https://docs.python.org/3/library/wave.html"],"relationship":"WAV, envelope, PSD and beta use exactly the same decoded PCM16 samples.","runtime":{"numpy":"2.5.4","scipy":"1.18.1"},"sample_rate_hz":8000,"samples":16384,"seeds":"Two fixed seeds per scenario, declared before generation; no selection by result.","welch":{"average":"mean","detrend":"linear","frequency_resolution_hz":3.90625,"nfft":2048,"one_sided":true,"overlap_samples":1024,"scaling":"density","segment_samples":2048,"window":"hann_periodic"}},"scenarios":[{"description":{"en":"Gaussian noise whose average power does not favour any frequency.","fr":"Un bruit gaussien dont la puissance moyenne ne privilégie aucune fréquence."},"id":"white","realizations":[{"audio":{"duration_seconds":2.048,"encoding":"PCM16 little-endian 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and noise","fr":"Oscillation et bruit"}}],"schema":"trinity.learning/1","sha256":"03eb21c1566182bb566e85701c0101c50bad62ae7ece87444a559d004f515482"}