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author | Daniel Baumann <daniel.baumann@progress-linux.org> | 2024-04-19 00:47:55 +0000 |
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committer | Daniel Baumann <daniel.baumann@progress-linux.org> | 2024-04-19 00:47:55 +0000 |
commit | 26a029d407be480d791972afb5975cf62c9360a6 (patch) | |
tree | f435a8308119effd964b339f76abb83a57c29483 /third_party/libwebrtc/modules/audio_processing/utility/delay_estimator.cc | |
parent | Initial commit. (diff) | |
download | firefox-26a029d407be480d791972afb5975cf62c9360a6.tar.xz firefox-26a029d407be480d791972afb5975cf62c9360a6.zip |
Adding upstream version 124.0.1.upstream/124.0.1
Signed-off-by: Daniel Baumann <daniel.baumann@progress-linux.org>
Diffstat (limited to 'third_party/libwebrtc/modules/audio_processing/utility/delay_estimator.cc')
-rw-r--r-- | third_party/libwebrtc/modules/audio_processing/utility/delay_estimator.cc | 708 |
1 files changed, 708 insertions, 0 deletions
diff --git a/third_party/libwebrtc/modules/audio_processing/utility/delay_estimator.cc b/third_party/libwebrtc/modules/audio_processing/utility/delay_estimator.cc new file mode 100644 index 0000000000..6868392f6f --- /dev/null +++ b/third_party/libwebrtc/modules/audio_processing/utility/delay_estimator.cc @@ -0,0 +1,708 @@ +/* + * Copyright (c) 2012 The WebRTC project authors. All Rights Reserved. + * + * Use of this source code is governed by a BSD-style license + * that can be found in the LICENSE file in the root of the source + * tree. An additional intellectual property rights grant can be found + * in the file PATENTS. All contributing project authors may + * be found in the AUTHORS file in the root of the source tree. + */ + +#include "modules/audio_processing/utility/delay_estimator.h" + +#include <stdlib.h> +#include <string.h> + +#include <algorithm> + +#include "rtc_base/checks.h" + +namespace webrtc { + +namespace { + +// Number of right shifts for scaling is linearly depending on number of bits in +// the far-end binary spectrum. +static const int kShiftsAtZero = 13; // Right shifts at zero binary spectrum. +static const int kShiftsLinearSlope = 3; + +static const int32_t kProbabilityOffset = 1024; // 2 in Q9. +static const int32_t kProbabilityLowerLimit = 8704; // 17 in Q9. +static const int32_t kProbabilityMinSpread = 2816; // 5.5 in Q9. + +// Robust validation settings +static const float kHistogramMax = 3000.f; +static const float kLastHistogramMax = 250.f; +static const float kMinHistogramThreshold = 1.5f; +static const int kMinRequiredHits = 10; +static const int kMaxHitsWhenPossiblyNonCausal = 10; +static const int kMaxHitsWhenPossiblyCausal = 1000; +static const float kQ14Scaling = 1.f / (1 << 14); // Scaling by 2^14 to get Q0. +static const float kFractionSlope = 0.05f; +static const float kMinFractionWhenPossiblyCausal = 0.5f; +static const float kMinFractionWhenPossiblyNonCausal = 0.25f; + +} // namespace + +// Counts and returns number of bits of a 32-bit word. +static int BitCount(uint32_t u32) { + uint32_t tmp = + u32 - ((u32 >> 1) & 033333333333) - ((u32 >> 2) & 011111111111); + tmp = ((tmp + (tmp >> 3)) & 030707070707); + tmp = (tmp + (tmp >> 6)); + tmp = (tmp + (tmp >> 12) + (tmp >> 24)) & 077; + + return ((int)tmp); +} + +// 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: +// - binary_vector : binary "vector" stored in a long +// - binary_matrix : binary "matrix" stored as a vector of long +// - matrix_size : size of binary "matrix" +// +// Output: +// - bit_counts : "Vector" stored as a long, containing for each +// row the number of times the matrix row and the +// input vector have the same value +// +static void BitCountComparison(uint32_t binary_vector, + const uint32_t* binary_matrix, + int matrix_size, + int32_t* bit_counts) { + int n = 0; + + // 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]); + } +} + +// 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 +// weighted with respect to a reliability measure and time-varying to cope +// with possible delay shifts. +// For further description see commented code. +// +// 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 +// 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. +static void UpdateRobustValidationStatistics(BinaryDelayEstimator* self, + int candidate_delay, + int32_t valley_depth_q14, + int32_t valley_level_q14) { + const float valley_depth = valley_depth_q14 * kQ14Scaling; + float decrease_in_last_set = valley_depth; + const int max_hits_for_slow_change = (candidate_delay < self->last_delay) + ? kMaxHitsWhenPossiblyNonCausal + : kMaxHitsWhenPossiblyCausal; + int i = 0; + + RTC_DCHECK_EQ(self->history_size, self->farend->history_size); + // 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`. + 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 + // 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`. + 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`. + // 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) { + int is_in_last_set = (i >= self->last_delay - 2) && + (i <= self->last_delay + 1) && (i != candidate_delay); + int is_in_candidate_set = + (i >= candidate_delay - 2) && (i <= candidate_delay + 1); + self->histogram[i] -= + decrease_in_last_set * is_in_last_set + + valley_depth * (!is_in_last_set && !is_in_candidate_set); + // 5. No histogram bin can go below 0. + if (self->histogram[i] < 0) { + self->histogram[i] = 0; + } + } +} + +// 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 +// 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. +// 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. +// If the delay difference is larger than what the filter can capture, we +// also move quicker towards a change. +// For further description see commented code. +// +// Input: +// - candidate_delay : The delay to validate. +// +// Return value: +// - is_histogram_valid : 1 - The `candidate_delay` is valid. +// 0 - Otherwise. +static int HistogramBasedValidation(const BinaryDelayEstimator* self, + int candidate_delay) { + float fraction = 1.f; + float histogram_threshold = self->histogram[self->compare_delay]; + 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` + // 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 + // 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 + // values. + + // 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) { + fraction = 1.f - kFractionSlope * (delay_difference - self->allowed_offset); + fraction = (fraction > kMinFractionWhenPossiblyCausal + ? fraction + : kMinFractionWhenPossiblyCausal); + } else if (delay_difference < 0) { + fraction = + kMinFractionWhenPossiblyNonCausal - kFractionSlope * delay_difference; + fraction = (fraction > 1.f ? 1.f : fraction); + } + histogram_threshold *= fraction; + histogram_threshold = + (histogram_threshold > kMinHistogramThreshold ? histogram_threshold + : kMinHistogramThreshold); + + is_histogram_valid = + (self->histogram[candidate_delay] >= histogram_threshold) && + (self->candidate_hits > kMinRequiredHits); + + return is_histogram_valid; +} + +// 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 +// 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. +// +// Inputs: +// - candidate_delay : The delay to validate. +// - is_instantaneous_valid : The instantaneous validation performed in +// WebRtc_ProcessBinarySpectrum(). +// - is_histogram_valid : The histogram based validation. +// +// Return value: +// - is_robust : 1 - The candidate_delay is valid according to a +// combination of the two inputs. +// : 0 - Otherwise. +static int RobustValidation(const BinaryDelayEstimator* self, + int candidate_delay, + int is_instantaneous_valid, + int is_histogram_valid) { + 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 + // a candidate is valid if either algorithm states so + // (`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_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 + // is significantly strong. + is_robust |= is_histogram_valid && + (self->histogram[candidate_delay] > self->last_delay_histogram); + + return is_robust; +} + +void WebRtc_FreeBinaryDelayEstimatorFarend(BinaryDelayEstimatorFarend* self) { + if (self == NULL) { + return; + } + + free(self->binary_far_history); + self->binary_far_history = NULL; + + free(self->far_bit_counts); + self->far_bit_counts = NULL; + + free(self); +} + +BinaryDelayEstimatorFarend* WebRtc_CreateBinaryDelayEstimatorFarend( + int history_size) { + BinaryDelayEstimatorFarend* self = NULL; + + if (history_size > 1) { + // Sanity conditions fulfilled. + self = static_cast<BinaryDelayEstimatorFarend*>( + malloc(sizeof(BinaryDelayEstimatorFarend))); + } + if (self == NULL) { + return NULL; + } + + self->history_size = 0; + self->binary_far_history = NULL; + self->far_bit_counts = NULL; + if (WebRtc_AllocateFarendBufferMemory(self, history_size) == 0) { + WebRtc_FreeBinaryDelayEstimatorFarend(self); + self = NULL; + } + return self; +} + +int WebRtc_AllocateFarendBufferMemory(BinaryDelayEstimatorFarend* self, + int history_size) { + RTC_DCHECK(self); + // (Re-)Allocate memory for history buffers. + self->binary_far_history = static_cast<uint32_t*>( + realloc(self->binary_far_history, + history_size * sizeof(*self->binary_far_history))); + self->far_bit_counts = static_cast<int*>(realloc( + self->far_bit_counts, history_size * sizeof(*self->far_bit_counts))); + if ((self->binary_far_history == NULL) || (self->far_bit_counts == NULL)) { + history_size = 0; + } + // Fill with zeros if we have expanded the buffers. + if (history_size > self->history_size) { + int size_diff = history_size - self->history_size; + memset(&self->binary_far_history[self->history_size], 0, + sizeof(*self->binary_far_history) * size_diff); + memset(&self->far_bit_counts[self->history_size], 0, + sizeof(*self->far_bit_counts) * size_diff); + } + self->history_size = history_size; + + return self->history_size; +} + +void WebRtc_InitBinaryDelayEstimatorFarend(BinaryDelayEstimatorFarend* self) { + RTC_DCHECK(self); + memset(self->binary_far_history, 0, sizeof(uint32_t) * self->history_size); + memset(self->far_bit_counts, 0, sizeof(int) * self->history_size); +} + +void WebRtc_SoftResetBinaryDelayEstimatorFarend( + BinaryDelayEstimatorFarend* self, + int delay_shift) { + int abs_shift = abs(delay_shift); + int shift_size = 0; + int dest_index = 0; + int src_index = 0; + int padding_index = 0; + + RTC_DCHECK(self); + shift_size = self->history_size - abs_shift; + RTC_DCHECK_GT(shift_size, 0); + if (delay_shift == 0) { + return; + } else if (delay_shift > 0) { + dest_index = abs_shift; + } else if (delay_shift < 0) { + src_index = abs_shift; + padding_index = shift_size; + } + + // Shift and zero pad buffers. + memmove(&self->binary_far_history[dest_index], + &self->binary_far_history[src_index], + sizeof(*self->binary_far_history) * shift_size); + memset(&self->binary_far_history[padding_index], 0, + sizeof(*self->binary_far_history) * abs_shift); + memmove(&self->far_bit_counts[dest_index], &self->far_bit_counts[src_index], + sizeof(*self->far_bit_counts) * shift_size); + memset(&self->far_bit_counts[padding_index], 0, + sizeof(*self->far_bit_counts) * abs_shift); +} + +void WebRtc_AddBinaryFarSpectrum(BinaryDelayEstimatorFarend* handle, + uint32_t binary_far_spectrum) { + RTC_DCHECK(handle); + // 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`. + 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); +} + +void WebRtc_FreeBinaryDelayEstimator(BinaryDelayEstimator* self) { + if (self == NULL) { + return; + } + + free(self->mean_bit_counts); + self->mean_bit_counts = NULL; + + free(self->bit_counts); + self->bit_counts = NULL; + + free(self->binary_near_history); + self->binary_near_history = NULL; + + free(self->histogram); + self->histogram = NULL; + + // 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; + + free(self); +} + +BinaryDelayEstimator* WebRtc_CreateBinaryDelayEstimator( + BinaryDelayEstimatorFarend* farend, + int max_lookahead) { + BinaryDelayEstimator* self = NULL; + + if ((farend != NULL) && (max_lookahead >= 0)) { + // Sanity conditions fulfilled. + self = static_cast<BinaryDelayEstimator*>( + malloc(sizeof(BinaryDelayEstimator))); + } + if (self == NULL) { + return NULL; + } + + self->farend = farend; + self->near_history_size = max_lookahead + 1; + self->history_size = 0; + self->robust_validation_enabled = 0; // Disabled by default. + self->allowed_offset = 0; + + self->lookahead = max_lookahead; + + // Allocate memory for spectrum and history buffers. + self->mean_bit_counts = NULL; + self->bit_counts = NULL; + self->histogram = NULL; + self->binary_near_history = static_cast<uint32_t*>( + malloc((max_lookahead + 1) * sizeof(*self->binary_near_history))); + if (self->binary_near_history == NULL || + WebRtc_AllocateHistoryBufferMemory(self, farend->history_size) == 0) { + WebRtc_FreeBinaryDelayEstimator(self); + self = NULL; + } + + return self; +} + +int WebRtc_AllocateHistoryBufferMemory(BinaryDelayEstimator* self, + int history_size) { + BinaryDelayEstimatorFarend* far = self->farend; + // (Re-)Allocate memory for spectrum and history buffers. + if (history_size != far->history_size) { + // 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 + // estimate. + self->mean_bit_counts = static_cast<int32_t*>( + realloc(self->mean_bit_counts, + (history_size + 1) * sizeof(*self->mean_bit_counts))); + self->bit_counts = static_cast<int32_t*>( + realloc(self->bit_counts, history_size * sizeof(*self->bit_counts))); + self->histogram = static_cast<float*>( + realloc(self->histogram, (history_size + 1) * sizeof(*self->histogram))); + + if ((self->mean_bit_counts == NULL) || (self->bit_counts == NULL) || + (self->histogram == NULL)) { + history_size = 0; + } + // Fill with zeros if we have expanded the buffers. + if (history_size > self->history_size) { + int size_diff = history_size - self->history_size; + memset(&self->mean_bit_counts[self->history_size], 0, + sizeof(*self->mean_bit_counts) * size_diff); + memset(&self->bit_counts[self->history_size], 0, + sizeof(*self->bit_counts) * size_diff); + memset(&self->histogram[self->history_size], 0, + sizeof(*self->histogram) * size_diff); + } + self->history_size = history_size; + + return self->history_size; +} + +void WebRtc_InitBinaryDelayEstimator(BinaryDelayEstimator* self) { + int i = 0; + RTC_DCHECK(self); + + memset(self->bit_counts, 0, sizeof(int32_t) * self->history_size); + memset(self->binary_near_history, 0, + sizeof(uint32_t) * self->near_history_size); + for (i = 0; i <= self->history_size; ++i) { + self->mean_bit_counts[i] = (20 << 9); // 20 in Q9. + self->histogram[i] = 0.f; + } + self->minimum_probability = kMaxBitCountsQ9; // 32 in Q9. + self->last_delay_probability = (int)kMaxBitCountsQ9; // 32 in Q9. + + // Default return value if we're unable to estimate. -1 is used for errors. + self->last_delay = -2; + + self->last_candidate_delay = -2; + self->compare_delay = self->history_size; + self->candidate_hits = 0; + self->last_delay_histogram = 0.f; +} + +int WebRtc_SoftResetBinaryDelayEstimator(BinaryDelayEstimator* self, + int delay_shift) { + int lookahead = 0; + RTC_DCHECK(self); + lookahead = self->lookahead; + self->lookahead -= delay_shift; + if (self->lookahead < 0) { + self->lookahead = 0; + } + if (self->lookahead > self->near_history_size - 1) { + self->lookahead = self->near_history_size - 1; + } + return lookahead - self->lookahead; +} + +int WebRtc_ProcessBinarySpectrum(BinaryDelayEstimator* self, + uint32_t binary_near_spectrum) { + int i = 0; + int candidate_delay = -1; + int valid_candidate = 0; + + int32_t value_best_candidate = kMaxBitCountsQ9; + int32_t value_worst_candidate = 0; + int32_t valley_depth = 0; + + RTC_DCHECK(self); + if (self->farend->history_size != self->history_size) { + // Non matching history sizes. + return -1; + } + 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. + 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. + 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`. + for (i = 0; i < self->history_size; i++) { + // `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 + // 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`. + 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`. + 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]; + candidate_delay = i; + } + if (self->mean_bit_counts[i] > value_worst_candidate) { + value_worst_candidate = self->mean_bit_counts[i]; + } + } + 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` + // means a good binary match). In the following sections we make a decision + // 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 + // 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 + // this time instant. + + // 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 + // to be large enough. + int32_t threshold = value_best_candidate + kProbabilityOffset; + if (threshold < kProbabilityLowerLimit) { + threshold = kProbabilityLowerLimit; + } + if (self->minimum_probability > threshold) { + self->minimum_probability = threshold; + } + } + // 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 + // estimate if + // 1) The valley is distinct enough (`valley_depth` > `kProbabilityOffset`) + // and + // 2) The depth of the valley is deep enough + // (`value_best_candidate` < `minimum_probability`) + // and deeper than the best estimate so far + // (`value_best_candidate` < `last_delay_probability`) + valid_candidate = ((valley_depth > kProbabilityOffset) && + ((value_best_candidate < self->minimum_probability) || + (value_best_candidate < self->last_delay_probability))); + + // Check for nonstationary farend signal. + const bool non_stationary_farend = + std::any_of(self->farend->far_bit_counts, + self->farend->far_bit_counts + self->history_size, + [](int a) { return a > 0; }); + + if (non_stationary_farend) { + // Only update the validation statistics when the farend is nonstationary + // as the underlying estimates are otherwise frozen. + UpdateRobustValidationStatistics(self, candidate_delay, valley_depth, + value_best_candidate); + } + + if (self->robust_validation_enabled) { + int is_histogram_valid = HistogramBasedValidation(self, candidate_delay); + valid_candidate = RobustValidation(self, candidate_delay, valid_candidate, + is_histogram_valid); + } + + // Only update the delay estimate when the farend is nonstationary and when + // a valid delay candidate is available. + if (non_stationary_farend && valid_candidate) { + if (candidate_delay != self->last_delay) { + self->last_delay_histogram = + (self->histogram[candidate_delay] > kLastHistogramMax + ? kLastHistogramMax + : self->histogram[candidate_delay]); + // 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]) { + self->histogram[self->compare_delay] = self->histogram[candidate_delay]; + } + } + self->last_delay = candidate_delay; + if (value_best_candidate < self->last_delay_probability) { + self->last_delay_probability = value_best_candidate; + } + self->compare_delay = self->last_delay; + } + + return self->last_delay; +} + +int WebRtc_binary_last_delay(BinaryDelayEstimator* self) { + RTC_DCHECK(self); + return self->last_delay; +} + +float WebRtc_binary_last_delay_quality(BinaryDelayEstimator* self) { + float quality = 0; + RTC_DCHECK(self); + + if (self->robust_validation_enabled) { + // 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 + // cost function is, so it is rather an error probability. + quality = (float)(kMaxBitCountsQ9 - self->last_delay_probability) / + kMaxBitCountsQ9; + if (quality < 0) { + quality = 0; + } + } + return quality; +} + +void WebRtc_MeanEstimatorFix(int32_t new_value, + int factor, + int32_t* mean_value) { + int32_t diff = new_value - *mean_value; + + // mean_new = mean_value + ((new_value - mean_value) >> factor); + if (diff < 0) { + diff = -((-diff) >> factor); + } else { + diff = (diff >> factor); + } + *mean_value += diff; +} + +} // namespace webrtc |