This function, `rnn_pitch_filter`, applies a filtering process in the frequency...

This function, rnn_pitch_filter, applies a filtering process in the frequency domain typically used for modifying or enhancing audio signals in applications like speech processing, noise suppression, or pitch filtering. Here's a breakdown of what the code does:

Key Steps:

1. Inputs:

   • kiss_fft_cpx *X: The current frequency-domain representation of the signal (complex values).
   • const kiss_fft_cpx *P: The pitch signal in the frequency domain (also complex values).
   • const float *Ex: Array representing the energy of the input signal in the frequency domain.
   • const float *Ep: Array representing the energy of the pitch signal in the frequency domain.
   • const float *Exp: Array representing the correlation between the signal and the pitch.
   • const float *g: Gain values or thresholds.

2. Compute r (band gain factors):

   • For each frequency band (controlled by NB_BANDS), a gain factor r[i] is calculated, which determines how strongly the pitch signal should influence the input signal.
   • If the pitch correlation Exp[i] is higher than the gain limit g[i], r[i] is set to 1 (maximum influence). Otherwise, it uses a formula involving squared values (Exp and g) to scale the gain for pitch correlation. The gain r[i] is clipped to ensure it's in the range [0, 1].
   • Additionally, r[i] is adjusted by the ratio of the input energy Ex[i] to the pitch energy Ep[i] using a square root to normalize the scaling.

3. Interpolate Gain for Each Frequency Bin:

   • The per-band gain factors r are interpolated over all frequency bins to form rf, representing smooth gain values for every frequency bin.
   • This interpolation is done by the interp_band_gain function (not provided in the snippet).

4. Modify the Input Signal with the Pitch Signal:

   • For every frequency bin i (controlled by FREQ_SIZE), the real and imaginary parts of the input spectrum X[i] are incremented by their corresponding components from the pitch signal P[i], scaled by the interpolated gain rf[i].

5. Normalize Energy of the Updated Signal:

   • The energy of the modified signal X is computed into newE across bands.
   • A normalization factor norm[i] is calculated per band, based on the ratio of original energy Ex[i] to the updated energy newE[i].
   • The band-wise normalization factors norm are interpolated across all frequency bins into normf.

6. Apply Normalization:

   • The reconstructed signal X is normalized in magnitude by multiplying all real and imaginary components by the interpolated normalization factors normf.

Purpose:

The primary goal of this code is to implement a frequency-domain adjustment that filters the input signal X based on its pitch correlation P while ensuring energy consistency. Here's what it does in context:

• Modifies the signal based on its relationship to a pitch signal, with adaptive gain control (r[i]).
• Ensures smooth transitions by interpolating band gains over individual frequency bins.
• Normalizes the filtered signal to maintain consistent energy levels.

Applications:

This type of processing is commonly used in:

• Speech enhancement: Aligns or emphasizes components of the signal based on pitch information, e.g., enhancing voiced speech.
• Audio source separation: Extracts specific sources corresponding to pitch or harmonic information.
• Noise suppression: Reduces noise by keeping the desired pitch-related components while suppressing others.