The provided C code is a helper function used in...
The provided C code is a helper function used in audio processing, particularly in finding the best pitch candidates to aid in tasks such as pitch detection, audio compression, or speech analysis. Let’s break down what this find_best_pitch
function does:
Purpose:
The function identifies the two best pitch candidates (best_pitch[0]
and best_pitch[1]
) from a cross-correlation analysis of an input signal. It compares all candidates based on specific criteria to determine the strongest periodic matches between segments of the signal.
Parameters:
-
opus_val32 *xcorr
: Precomputed cross-correlation values for the signal, passed as an array. -
opus_val16 *y
: The signal data for which pitch is being analyzed. -
int len
: The length of the segment being analyzed. -
int max_pitch
: The maximum pitch period to consider. It limits the range of pitch candidates. -
int *best_pitch
: The output array that stores the two best pitch candidates (index values ofxcorr
).Optional (FIXED_POINT specific): 6.
int yshift
: A scaling factor used in fixed-point arithmetic to manage precision. 7.opus_val32 maxcorr
: The maximum cross-correlation value, used to normalize computation for fixed-point mode.
Breakdown of Function Logic:
-
Initialization:
- The function initializes variables like
Syy
to start with a value of 1. - Arrays
best_num
andbest_den
are initialized to hold numerators and denominators of the scoring metric for the two best pitch candidates.
- The function initializes variables like
-
Compute Signal Energy (Syy):
Syy
is initialized by summing the squared values of the signaly
over the segment lengthlen
.- This is part of the normalization process to ensure correlation values are scaled relative to signal energy.
-
Iterate Over Pitch Candidates:
- The primary loop iterates over all pitch candidates from 0 to
max_pitch - 1
. - If the cross-correlation (
xcorr[i]
) for a pitch candidate is positive, the function proceeds to compute its score.
- The primary loop iterates over all pitch candidates from 0 to
-
Score Calculation:
- The function calculates a score for the current pitch candidate, which involves squaring the normalized cross-correlation value (
xcorr16
) and comparing it to previously identified best scores. - The score is evaluated using the formula:
(num / den)
wherenum
is the square of the normalized cross-correlation, andden
is the energySyy
. - If the current score is better than the second-best (
best_num[1]
), it updates the list of best pitch candidates.
- The function calculates a score for the current pitch candidate, which involves squaring the normalized cross-correlation value (
-
Sliding Window Update:
- The energy
Syy
is updated in a sliding-window manner as the loop progresses. For the next pitch candidate, it subtracts the squared value of the signal element leaving the window (y[i]
) and adds the squared value of the new element entering the window (y[i + len]
). Syy
is clamped to a minimum of 1 to avoid division by zero or overly small values.
- The energy
-
Best Pitch Results:
- At the end of the loop, the top two pitch candidates (based on the score) are stored in the
best_pitch
array.
- At the end of the loop, the top two pitch candidates (based on the score) are stored in the
Key Details:
-
Fixed-Point and Floating-Point Modes:
- The function is designed to work in both fixed-point and floating-point environments, depending on whether the
FIXED_POINT
macro is defined. - In fixed-point mode, additional calculations involving
yshift
andxshift
are used to manage precision and scaling.
- The function is designed to work in both fixed-point and floating-point environments, depending on whether the
-
Numerical Stability:
- To avoid issues such as overflow, underflow, or division by small numbers, the function clamps or scales values (e.g.,
Syy = MAX32(1, Syy)
).
- To avoid issues such as overflow, underflow, or division by small numbers, the function clamps or scales values (e.g.,
What Does This Code Achieve?
This code is specifically designed to detect the most likely pitch periods for a given signal based on the precomputed cross-correlation values. It ensures robust detection by normalizing scores and handling edge cases like low energy. Such functionality is commonly found in low-level audio codecs or analysis tools like Opus, where pitch estimation is used for encoding, decoding, or enhancing audio signals.