Statistical analysis (ANOVA, p < 0.01) confirms that DFX‑AE (default) yields a significant improvement over the original and the competitor across all categories.
where T_b is the band‑specific threshold and α_b controls the knee curvature. The RMS detector uses a 50 ms smoothing window. The final output for band b is
[ y_b[n] = G_b[n] \cdot x_b[n]. ]
[ L'[n] = M[n] + S'[n],\qquad R'[n] = M[n] - S'[n]. ] A perceptual loudness model based on the ITU‑R BS.1770‑4 algorithm computes the integrated loudness L_int over a 400 ms window. The target loudness L_target (default = –14 LUFS) determines a gain factor
[ G_b[n] = 1 - \frac11 + \left(\frac\lVert x_b[n]\rVert_\mathrmRMST_b\right)^\alpha_b, ] dfx audio enhancer full
[ S'(n) = g_S(f) \cdot D\bigl(S[n]\bigr), ]
Cross‑fading between adjacent bands uses a cosine‑squared window to avoid discontinuities. The exciter applies a non‑linear function f(·) followed by a high‑shelf filter H_s(·) : Statistical analysis (ANOVA, p < 0
[Your Name], [Affiliation] – Department of Electrical Engineering & Computer Science [Co‑author Name], [Affiliation] – Institute for Audio Research