AnotherFoxGuy/webrtc-audio-processing
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Bump to WebRTC M120 release

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Some API deprecation -- ExperimentalAgc and ExperimentalNs are gone.
We're continuing to carry iSAC even though it's gone upstream, but maybe
we'll want to drop that soon.
This commit is contained in:
Arun Raghavan
2023-12-12 10:42:58 -05:00
parent 9a202fb8c2
commit c6abf6cd3f
479 changed files with 20900 additions and 11996 deletions
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146
webrtc/modules/audio_processing/utility/delay_estimator.cc
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@ -55,7 +55,7 @@ static int BitCount(uint32_t u32) {
return ((int)tmp);
}
// Compares the |binary_vector| with all rows of the |binary_matrix| and counts
// Compares the `binary_vector` with all rows of the `binary_matrix` and counts
// per row the number of times they have the same value.
//
// Inputs:
@ -74,7 +74,7 @@ static void BitCountComparison(uint32_t binary_vector,
int32_t* bit_counts) {
int n = 0;
// Compare |binary_vector| with all rows of the |binary_matrix|
// Compare `binary_vector` with all rows of the `binary_matrix`
for (; n < matrix_size; n++) {
bit_counts[n] = (int32_t)BitCount(binary_vector ^ binary_matrix[n]);
}
@ -83,9 +83,9 @@ static void BitCountComparison(uint32_t binary_vector,
// Collects necessary statistics for the HistogramBasedValidation(). This
// function has to be called prior to calling HistogramBasedValidation(). The
// statistics updated and used by the HistogramBasedValidation() are:
// 1. the number of |candidate_hits|, which states for how long we have had the
// same |candidate_delay|
// 2. the |histogram| of candidate delays over time. This histogram is
// 1. the number of `candidate_hits`, which states for how long we have had the
// same `candidate_delay`
// 2. the `histogram` of candidate delays over time. This histogram is
// weighted with respect to a reliability measure and time-varying to cope
// with possible delay shifts.
// For further description see commented code.
@ -93,7 +93,7 @@ static void BitCountComparison(uint32_t binary_vector,
// Inputs:
// - candidate_delay : The delay to validate.
// - valley_depth_q14 : The cost function has a valley/minimum at the
// |candidate_delay| location. |valley_depth_q14| is the
// `candidate_delay` location. `valley_depth_q14` is the
// cost function difference between the minimum and
// maximum locations. The value is in the Q14 domain.
// - valley_level_q14 : Is the cost function value at the minimum, in Q14.
@ -109,37 +109,37 @@ static void UpdateRobustValidationStatistics(BinaryDelayEstimator* self,
int i = 0;
RTC_DCHECK_EQ(self->history_size, self->farend->history_size);
// Reset |candidate_hits| if we have a new candidate.
// Reset `candidate_hits` if we have a new candidate.
if (candidate_delay != self->last_candidate_delay) {
self->candidate_hits = 0;
self->last_candidate_delay = candidate_delay;
}
self->candidate_hits++;
// The |histogram| is updated differently across the bins.
// 1. The |candidate_delay| histogram bin is increased with the
// |valley_depth|, which is a simple measure of how reliable the
// |candidate_delay| is. The histogram is not increased above
// |kHistogramMax|.
// The `histogram` is updated differently across the bins.
// 1. The `candidate_delay` histogram bin is increased with the
// `valley_depth`, which is a simple measure of how reliable the
// `candidate_delay` is. The histogram is not increased above
// `kHistogramMax`.
self->histogram[candidate_delay] += valley_depth;
if (self->histogram[candidate_delay] > kHistogramMax) {
self->histogram[candidate_delay] = kHistogramMax;
}
// 2. The histogram bins in the neighborhood of |candidate_delay| are
// 2. The histogram bins in the neighborhood of `candidate_delay` are
// unaffected. The neighborhood is defined as x + {-2, -1, 0, 1}.
// 3. The histogram bins in the neighborhood of |last_delay| are decreased
// with |decrease_in_last_set|. This value equals the difference between
// the cost function values at the locations |candidate_delay| and
// |last_delay| until we reach |max_hits_for_slow_change| consecutive hits
// at the |candidate_delay|. If we exceed this amount of hits the
// |candidate_delay| is a "potential" candidate and we start decreasing
// these histogram bins more rapidly with |valley_depth|.
// 3. The histogram bins in the neighborhood of `last_delay` are decreased
// with `decrease_in_last_set`. This value equals the difference between
// the cost function values at the locations `candidate_delay` and
// `last_delay` until we reach `max_hits_for_slow_change` consecutive hits
// at the `candidate_delay`. If we exceed this amount of hits the
// `candidate_delay` is a "potential" candidate and we start decreasing
// these histogram bins more rapidly with `valley_depth`.
if (self->candidate_hits < max_hits_for_slow_change) {
decrease_in_last_set =
(self->mean_bit_counts[self->compare_delay] - valley_level_q14) *
kQ14Scaling;
}
// 4. All other bins are decreased with |valley_depth|.
// 4. All other bins are decreased with `valley_depth`.
// TODO(bjornv): Investigate how to make this loop more efficient. Split up
// the loop? Remove parts that doesn't add too much.
for (i = 0; i < self->history_size; ++i) {
@ -157,15 +157,15 @@ static void UpdateRobustValidationStatistics(BinaryDelayEstimator* self,
}
}
// Validates the |candidate_delay|, estimated in WebRtc_ProcessBinarySpectrum(),
// Validates the `candidate_delay`, estimated in WebRtc_ProcessBinarySpectrum(),
// based on a mix of counting concurring hits with a modified histogram
// of recent delay estimates. In brief a candidate is valid (returns 1) if it
// is the most likely according to the histogram. There are a couple of
// exceptions that are worth mentioning:
// 1. If the |candidate_delay| < |last_delay| it can be that we are in a
// 1. If the `candidate_delay` < `last_delay` it can be that we are in a
// non-causal state, breaking a possible echo control algorithm. Hence, we
// open up for a quicker change by allowing the change even if the
// |candidate_delay| is not the most likely one according to the histogram.
// `candidate_delay` is not the most likely one according to the histogram.
// 2. There's a minimum number of hits (kMinRequiredHits) and the histogram
// value has to reached a minimum (kMinHistogramThreshold) to be valid.
// 3. The action is also depending on the filter length used for echo control.
@ -177,7 +177,7 @@ static void UpdateRobustValidationStatistics(BinaryDelayEstimator* self,
// - candidate_delay : The delay to validate.
//
// Return value:
// - is_histogram_valid : 1 - The |candidate_delay| is valid.
// - is_histogram_valid : 1 - The `candidate_delay` is valid.
// 0 - Otherwise.
static int HistogramBasedValidation(const BinaryDelayEstimator* self,
int candidate_delay) {
@ -186,22 +186,22 @@ static int HistogramBasedValidation(const BinaryDelayEstimator* self,
const int delay_difference = candidate_delay - self->last_delay;
int is_histogram_valid = 0;
// The histogram based validation of |candidate_delay| is done by comparing
// the |histogram| at bin |candidate_delay| with a |histogram_threshold|.
// This |histogram_threshold| equals a |fraction| of the |histogram| at bin
// |last_delay|. The |fraction| is a piecewise linear function of the
// |delay_difference| between the |candidate_delay| and the |last_delay|
// The histogram based validation of `candidate_delay` is done by comparing
// the `histogram` at bin `candidate_delay` with a `histogram_threshold`.
// This `histogram_threshold` equals a `fraction` of the `histogram` at bin
// `last_delay`. The `fraction` is a piecewise linear function of the
// `delay_difference` between the `candidate_delay` and the `last_delay`
// allowing for a quicker move if
// i) a potential echo control filter can not handle these large differences.
// ii) keeping |last_delay| instead of updating to |candidate_delay| could
// ii) keeping `last_delay` instead of updating to `candidate_delay` could
// force an echo control into a non-causal state.
// We further require the histogram to have reached a minimum value of
// |kMinHistogramThreshold|. In addition, we also require the number of
// |candidate_hits| to be more than |kMinRequiredHits| to remove spurious
// `kMinHistogramThreshold`. In addition, we also require the number of
// `candidate_hits` to be more than `kMinRequiredHits` to remove spurious
// values.
// Calculate a comparison histogram value (|histogram_threshold|) that is
// depending on the distance between the |candidate_delay| and |last_delay|.
// Calculate a comparison histogram value (`histogram_threshold`) that is
// depending on the distance between the `candidate_delay` and `last_delay`.
// TODO(bjornv): How much can we gain by turning the fraction calculation
// into tables?
if (delay_difference > self->allowed_offset) {
@ -226,9 +226,9 @@ static int HistogramBasedValidation(const BinaryDelayEstimator* self,
return is_histogram_valid;
}
// Performs a robust validation of the |candidate_delay| estimated in
// Performs a robust validation of the `candidate_delay` estimated in
// WebRtc_ProcessBinarySpectrum(). The algorithm takes the
// |is_instantaneous_valid| and the |is_histogram_valid| and combines them
// `is_instantaneous_valid` and the `is_histogram_valid` and combines them
// into a robust validation. The HistogramBasedValidation() has to be called
// prior to this call.
// For further description on how the combination is done, see commented code.
@ -250,18 +250,18 @@ static int RobustValidation(const BinaryDelayEstimator* self,
int is_robust = 0;
// The final robust validation is based on the two algorithms; 1) the
// |is_instantaneous_valid| and 2) the histogram based with result stored in
// |is_histogram_valid|.
// i) Before we actually have a valid estimate (|last_delay| == -2), we say
// `is_instantaneous_valid` and 2) the histogram based with result stored in
// `is_histogram_valid`.
// i) Before we actually have a valid estimate (`last_delay` == -2), we say
// a candidate is valid if either algorithm states so
// (|is_instantaneous_valid| OR |is_histogram_valid|).
// (`is_instantaneous_valid` OR `is_histogram_valid`).
is_robust =
(self->last_delay < 0) && (is_instantaneous_valid || is_histogram_valid);
// ii) Otherwise, we need both algorithms to be certain
// (|is_instantaneous_valid| AND |is_histogram_valid|)
// (`is_instantaneous_valid` AND `is_histogram_valid`)
is_robust |= is_instantaneous_valid && is_histogram_valid;
// iii) With one exception, i.e., the histogram based algorithm can overrule
// the instantaneous one if |is_histogram_valid| = 1 and the histogram
// the instantaneous one if `is_histogram_valid` = 1 and the histogram
// is significantly strong.
is_robust |= is_histogram_valid &&
(self->histogram[candidate_delay] > self->last_delay_histogram);
@ -373,13 +373,13 @@ void WebRtc_SoftResetBinaryDelayEstimatorFarend(
void WebRtc_AddBinaryFarSpectrum(BinaryDelayEstimatorFarend* handle,
uint32_t binary_far_spectrum) {
RTC_DCHECK(handle);
// Shift binary spectrum history and insert current |binary_far_spectrum|.
// Shift binary spectrum history and insert current `binary_far_spectrum`.
memmove(&(handle->binary_far_history[1]), &(handle->binary_far_history[0]),
(handle->history_size - 1) * sizeof(uint32_t));
handle->binary_far_history[0] = binary_far_spectrum;
// Shift history of far-end binary spectrum bit counts and insert bit count
// of current |binary_far_spectrum|.
// of current `binary_far_spectrum`.
memmove(&(handle->far_bit_counts[1]), &(handle->far_bit_counts[0]),
(handle->history_size - 1) * sizeof(int));
handle->far_bit_counts[0] = BitCount(binary_far_spectrum);
@ -402,7 +402,7 @@ void WebRtc_FreeBinaryDelayEstimator(BinaryDelayEstimator* self) {
free(self->histogram);
self->histogram = NULL;
// BinaryDelayEstimator does not have ownership of |farend|, hence we do not
// BinaryDelayEstimator does not have ownership of `farend`, hence we do not
// free the memory here. That should be handled separately by the user.
self->farend = NULL;
@ -454,8 +454,8 @@ int WebRtc_AllocateHistoryBufferMemory(BinaryDelayEstimator* self,
// Only update far-end buffers if we need.
history_size = WebRtc_AllocateFarendBufferMemory(far, history_size);
}
// The extra array element in |mean_bit_counts| and |histogram| is a dummy
// element only used while |last_delay| == -2, i.e., before we have a valid
// The extra array element in `mean_bit_counts` and `histogram` is a dummy
// element only used while `last_delay` == -2, i.e., before we have a valid
// estimate.
self->mean_bit_counts = static_cast<int32_t*>(
realloc(self->mean_bit_counts,
@ -539,36 +539,36 @@ int WebRtc_ProcessBinarySpectrum(BinaryDelayEstimator* self,
}
if (self->near_history_size > 1) {
// If we apply lookahead, shift near-end binary spectrum history. Insert
// current |binary_near_spectrum| and pull out the delayed one.
// current `binary_near_spectrum` and pull out the delayed one.
memmove(&(self->binary_near_history[1]), &(self->binary_near_history[0]),
(self->near_history_size - 1) * sizeof(uint32_t));
self->binary_near_history[0] = binary_near_spectrum;
binary_near_spectrum = self->binary_near_history[self->lookahead];
}
// Compare with delayed spectra and store the |bit_counts| for each delay.
// Compare with delayed spectra and store the `bit_counts` for each delay.
BitCountComparison(binary_near_spectrum, self->farend->binary_far_history,
self->history_size, self->bit_counts);
// Update |mean_bit_counts|, which is the smoothed version of |bit_counts|.
// Update `mean_bit_counts`, which is the smoothed version of `bit_counts`.
for (i = 0; i < self->history_size; i++) {
// |bit_counts| is constrained to [0, 32], meaning we can smooth with a
// `bit_counts` is constrained to [0, 32], meaning we can smooth with a
// factor up to 2^26. We use Q9.
int32_t bit_count = (self->bit_counts[i] << 9); // Q9.
// Update |mean_bit_counts| only when far-end signal has something to
// contribute. If |far_bit_counts| is zero the far-end signal is weak and
// Update `mean_bit_counts` only when far-end signal has something to
// contribute. If `far_bit_counts` is zero the far-end signal is weak and
// we likely have a poor echo condition, hence don't update.
if (self->farend->far_bit_counts[i] > 0) {
// Make number of right shifts piecewise linear w.r.t. |far_bit_counts|.
// Make number of right shifts piecewise linear w.r.t. `far_bit_counts`.
int shifts = kShiftsAtZero;
shifts -= (kShiftsLinearSlope * self->farend->far_bit_counts[i]) >> 4;
WebRtc_MeanEstimatorFix(bit_count, shifts, &(self->mean_bit_counts[i]));
}
}
// Find |candidate_delay|, |value_best_candidate| and |value_worst_candidate|
// of |mean_bit_counts|.
// Find `candidate_delay`, `value_best_candidate` and `value_worst_candidate`
// of `mean_bit_counts`.
for (i = 0; i < self->history_size; i++) {
if (self->mean_bit_counts[i] < value_best_candidate) {
value_best_candidate = self->mean_bit_counts[i];
@ -580,25 +580,25 @@ int WebRtc_ProcessBinarySpectrum(BinaryDelayEstimator* self,
}
valley_depth = value_worst_candidate - value_best_candidate;
// The |value_best_candidate| is a good indicator on the probability of
// |candidate_delay| being an accurate delay (a small |value_best_candidate|
// The `value_best_candidate` is a good indicator on the probability of
// `candidate_delay` being an accurate delay (a small `value_best_candidate`
// means a good binary match). In the following sections we make a decision
// whether to update |last_delay| or not.
// whether to update `last_delay` or not.
// 1) If the difference bit counts between the best and the worst delay
// candidates is too small we consider the situation to be unreliable and
// don't update |last_delay|.
// 2) If the situation is reliable we update |last_delay| if the value of the
// don't update `last_delay`.
// 2) If the situation is reliable we update `last_delay` if the value of the
// best candidate delay has a value less than
// i) an adaptive threshold |minimum_probability|, or
// ii) this corresponding value |last_delay_probability|, but updated at
// i) an adaptive threshold `minimum_probability`, or
// ii) this corresponding value `last_delay_probability`, but updated at
// this time instant.
// Update |minimum_probability|.
// Update `minimum_probability`.
if ((self->minimum_probability > kProbabilityLowerLimit) &&
(valley_depth > kProbabilityMinSpread)) {
// The "hard" threshold can't be lower than 17 (in Q9).
// The valley in the curve also has to be distinct, i.e., the
// difference between |value_worst_candidate| and |value_best_candidate| has
// difference between `value_worst_candidate` and `value_best_candidate` has
// to be large enough.
int32_t threshold = value_best_candidate + kProbabilityOffset;
if (threshold < kProbabilityLowerLimit) {
@ -608,17 +608,17 @@ int WebRtc_ProcessBinarySpectrum(BinaryDelayEstimator* self,
self->minimum_probability = threshold;
}
}
// Update |last_delay_probability|.
// Update `last_delay_probability`.
// We use a Markov type model, i.e., a slowly increasing level over time.
self->last_delay_probability++;
// Validate |candidate_delay|. We have a reliable instantaneous delay
// Validate `candidate_delay`. We have a reliable instantaneous delay
// estimate if
// 1) The valley is distinct enough (|valley_depth| > |kProbabilityOffset|)
// 1) The valley is distinct enough (`valley_depth` > `kProbabilityOffset`)
// and
// 2) The depth of the valley is deep enough
// (|value_best_candidate| < |minimum_probability|)
// (`value_best_candidate` < `minimum_probability`)
// and deeper than the best estimate so far
// (|value_best_candidate| < |last_delay_probability|)
// (`value_best_candidate` < `last_delay_probability`)
valid_candidate = ((valley_depth > kProbabilityOffset) &&
((value_best_candidate < self->minimum_probability) ||
(value_best_candidate < self->last_delay_probability)));
@ -650,7 +650,7 @@ int WebRtc_ProcessBinarySpectrum(BinaryDelayEstimator* self,
(self->histogram[candidate_delay] > kLastHistogramMax
? kLastHistogramMax
: self->histogram[candidate_delay]);
// Adjust the histogram if we made a change to |last_delay|, though it was
// Adjust the histogram if we made a change to `last_delay`, though it was
// not the most likely one according to the histogram.
if (self->histogram[candidate_delay] <
self->histogram[self->compare_delay]) {
@ -680,7 +680,7 @@ float WebRtc_binary_last_delay_quality(BinaryDelayEstimator* self) {
// Simply a linear function of the histogram height at delay estimate.
quality = self->histogram[self->compare_delay] / kHistogramMax;
} else {
// Note that |last_delay_probability| states how deep the minimum of the
// Note that `last_delay_probability` states how deep the minimum of the
// cost function is, so it is rather an error probability.
quality = (float)(kMaxBitCountsQ9 - self->last_delay_probability) /
kMaxBitCountsQ9;