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1 /*
2  *  Copyright (c) 2012 The WebRTC project authors. All Rights Reserved.
3  *
4  *  Use of this source code is governed by a BSD-style license
5  *  that can be found in the LICENSE file in the root of the source
6  *  tree. An additional intellectual property rights grant can be found
7  *  in the file PATENTS.  All contributing project authors may
8  *  be found in the AUTHORS file in the root of the source tree.
9  */
10 
11 #include "webrtc/modules/audio_processing/utility/delay_estimator.h"
12 
13 #include <assert.h>
14 #include <stdlib.h>
15 #include <string.h>
16 
17 // Number of right shifts for scaling is linearly depending on number of bits in
18 // the far-end binary spectrum.
19 static const int kShiftsAtZero = 13;  // Right shifts at zero binary spectrum.
20 static const int kShiftsLinearSlope = 3;
21 
22 static const int32_t kProbabilityOffset = 1024;  // 2 in Q9.
23 static const int32_t kProbabilityLowerLimit = 8704;  // 17 in Q9.
24 static const int32_t kProbabilityMinSpread = 2816;  // 5.5 in Q9.
25 
26 // Robust validation settings
27 static const float kHistogramMax = 3000.f;
28 static const float kLastHistogramMax = 250.f;
29 static const float kMinHistogramThreshold = 1.5f;
30 static const int kMinRequiredHits = 10;
31 static const int kMaxHitsWhenPossiblyNonCausal = 10;
32 static const int kMaxHitsWhenPossiblyCausal = 1000;
33 static const float kQ14Scaling = 1.f / (1 << 14);  // Scaling by 2^14 to get Q0.
34 static const float kFractionSlope = 0.05f;
35 static const float kMinFractionWhenPossiblyCausal = 0.5f;
36 static const float kMinFractionWhenPossiblyNonCausal = 0.25f;
37 
38 // Counts and returns number of bits of a 32-bit word.
BitCount(uint32_t u32)39 static int BitCount(uint32_t u32) {
40   uint32_t tmp = u32 - ((u32 >> 1) & 033333333333) -
41       ((u32 >> 2) & 011111111111);
42   tmp = ((tmp + (tmp >> 3)) & 030707070707);
43   tmp = (tmp + (tmp >> 6));
44   tmp = (tmp + (tmp >> 12) + (tmp >> 24)) & 077;
45 
46   return ((int) tmp);
47 }
48 
49 // Compares the |binary_vector| with all rows of the |binary_matrix| and counts
50 // per row the number of times they have the same value.
51 //
52 // Inputs:
53 //      - binary_vector     : binary "vector" stored in a long
54 //      - binary_matrix     : binary "matrix" stored as a vector of long
55 //      - matrix_size       : size of binary "matrix"
56 //
57 // Output:
58 //      - bit_counts        : "Vector" stored as a long, containing for each
59 //                            row the number of times the matrix row and the
60 //                            input vector have the same value
61 //
BitCountComparison(uint32_t binary_vector,const uint32_t * binary_matrix,int matrix_size,int32_t * bit_counts)62 static void BitCountComparison(uint32_t binary_vector,
63                                const uint32_t* binary_matrix,
64                                int matrix_size,
65                                int32_t* bit_counts) {
66   int n = 0;
67 
68   // Compare |binary_vector| with all rows of the |binary_matrix|
69   for (; n < matrix_size; n++) {
70     bit_counts[n] = (int32_t) BitCount(binary_vector ^ binary_matrix[n]);
71   }
72 }
73 
74 // Collects necessary statistics for the HistogramBasedValidation().  This
75 // function has to be called prior to calling HistogramBasedValidation().  The
76 // statistics updated and used by the HistogramBasedValidation() are:
77 //  1. the number of |candidate_hits|, which states for how long we have had the
78 //     same |candidate_delay|
79 //  2. the |histogram| of candidate delays over time.  This histogram is
80 //     weighted with respect to a reliability measure and time-varying to cope
81 //     with possible delay shifts.
82 // For further description see commented code.
83 //
84 // Inputs:
85 //  - candidate_delay   : The delay to validate.
86 //  - valley_depth_q14  : The cost function has a valley/minimum at the
87 //                        |candidate_delay| location.  |valley_depth_q14| is the
88 //                        cost function difference between the minimum and
89 //                        maximum locations.  The value is in the Q14 domain.
90 //  - valley_level_q14  : Is the cost function value at the minimum, in Q14.
UpdateRobustValidationStatistics(BinaryDelayEstimator * self,int candidate_delay,int32_t valley_depth_q14,int32_t valley_level_q14)91 static void UpdateRobustValidationStatistics(BinaryDelayEstimator* self,
92                                              int candidate_delay,
93                                              int32_t valley_depth_q14,
94                                              int32_t valley_level_q14) {
95   const float valley_depth = valley_depth_q14 * kQ14Scaling;
96   float decrease_in_last_set = valley_depth;
97   const int max_hits_for_slow_change = (candidate_delay < self->last_delay) ?
98       kMaxHitsWhenPossiblyNonCausal : kMaxHitsWhenPossiblyCausal;
99   int i = 0;
100 
101   assert(self->history_size == self->farend->history_size);
102   // Reset |candidate_hits| if we have a new candidate.
103   if (candidate_delay != self->last_candidate_delay) {
104     self->candidate_hits = 0;
105     self->last_candidate_delay = candidate_delay;
106   }
107   self->candidate_hits++;
108 
109   // The |histogram| is updated differently across the bins.
110   // 1. The |candidate_delay| histogram bin is increased with the
111   //    |valley_depth|, which is a simple measure of how reliable the
112   //    |candidate_delay| is.  The histogram is not increased above
113   //    |kHistogramMax|.
114   self->histogram[candidate_delay] += valley_depth;
115   if (self->histogram[candidate_delay] > kHistogramMax) {
116     self->histogram[candidate_delay] = kHistogramMax;
117   }
118   // 2. The histogram bins in the neighborhood of |candidate_delay| are
119   //    unaffected.  The neighborhood is defined as x + {-2, -1, 0, 1}.
120   // 3. The histogram bins in the neighborhood of |last_delay| are decreased
121   //    with |decrease_in_last_set|.  This value equals the difference between
122   //    the cost function values at the locations |candidate_delay| and
123   //    |last_delay| until we reach |max_hits_for_slow_change| consecutive hits
124   //    at the |candidate_delay|.  If we exceed this amount of hits the
125   //    |candidate_delay| is a "potential" candidate and we start decreasing
126   //    these histogram bins more rapidly with |valley_depth|.
127   if (self->candidate_hits < max_hits_for_slow_change) {
128     decrease_in_last_set = (self->mean_bit_counts[self->compare_delay] -
129         valley_level_q14) * kQ14Scaling;
130   }
131   // 4. All other bins are decreased with |valley_depth|.
132   // TODO(bjornv): Investigate how to make this loop more efficient.  Split up
133   // the loop?  Remove parts that doesn't add too much.
134   for (i = 0; i < self->history_size; ++i) {
135     int is_in_last_set = (i >= self->last_delay - 2) &&
136         (i <= self->last_delay + 1) && (i != candidate_delay);
137     int is_in_candidate_set = (i >= candidate_delay - 2) &&
138         (i <= candidate_delay + 1);
139     self->histogram[i] -= decrease_in_last_set * is_in_last_set +
140         valley_depth * (!is_in_last_set && !is_in_candidate_set);
141     // 5. No histogram bin can go below 0.
142     if (self->histogram[i] < 0) {
143       self->histogram[i] = 0;
144     }
145   }
146 }
147 
148 // Validates the |candidate_delay|, estimated in WebRtc_ProcessBinarySpectrum(),
149 // based on a mix of counting concurring hits with a modified histogram
150 // of recent delay estimates.  In brief a candidate is valid (returns 1) if it
151 // is the most likely according to the histogram.  There are a couple of
152 // exceptions that are worth mentioning:
153 //  1. If the |candidate_delay| < |last_delay| it can be that we are in a
154 //     non-causal state, breaking a possible echo control algorithm.  Hence, we
155 //     open up for a quicker change by allowing the change even if the
156 //     |candidate_delay| is not the most likely one according to the histogram.
157 //  2. There's a minimum number of hits (kMinRequiredHits) and the histogram
158 //     value has to reached a minimum (kMinHistogramThreshold) to be valid.
159 //  3. The action is also depending on the filter length used for echo control.
160 //     If the delay difference is larger than what the filter can capture, we
161 //     also move quicker towards a change.
162 // For further description see commented code.
163 //
164 // Input:
165 //  - candidate_delay     : The delay to validate.
166 //
167 // Return value:
168 //  - is_histogram_valid  : 1 - The |candidate_delay| is valid.
169 //                          0 - Otherwise.
HistogramBasedValidation(const BinaryDelayEstimator * self,int candidate_delay)170 static int HistogramBasedValidation(const BinaryDelayEstimator* self,
171                                     int candidate_delay) {
172   float fraction = 1.f;
173   float histogram_threshold = self->histogram[self->compare_delay];
174   const int delay_difference = candidate_delay - self->last_delay;
175   int is_histogram_valid = 0;
176 
177   // The histogram based validation of |candidate_delay| is done by comparing
178   // the |histogram| at bin |candidate_delay| with a |histogram_threshold|.
179   // This |histogram_threshold| equals a |fraction| of the |histogram| at bin
180   // |last_delay|.  The |fraction| is a piecewise linear function of the
181   // |delay_difference| between the |candidate_delay| and the |last_delay|
182   // allowing for a quicker move if
183   //  i) a potential echo control filter can not handle these large differences.
184   // ii) keeping |last_delay| instead of updating to |candidate_delay| could
185   //     force an echo control into a non-causal state.
186   // We further require the histogram to have reached a minimum value of
187   // |kMinHistogramThreshold|.  In addition, we also require the number of
188   // |candidate_hits| to be more than |kMinRequiredHits| to remove spurious
189   // values.
190 
191   // Calculate a comparison histogram value (|histogram_threshold|) that is
192   // depending on the distance between the |candidate_delay| and |last_delay|.
193   // TODO(bjornv): How much can we gain by turning the fraction calculation
194   // into tables?
195   if (delay_difference > self->allowed_offset) {
196     fraction = 1.f - kFractionSlope * (delay_difference - self->allowed_offset);
197     fraction = (fraction > kMinFractionWhenPossiblyCausal ? fraction :
198         kMinFractionWhenPossiblyCausal);
199   } else if (delay_difference < 0) {
200     fraction = kMinFractionWhenPossiblyNonCausal -
201         kFractionSlope * delay_difference;
202     fraction = (fraction > 1.f ? 1.f : fraction);
203   }
204   histogram_threshold *= fraction;
205   histogram_threshold = (histogram_threshold > kMinHistogramThreshold ?
206       histogram_threshold : kMinHistogramThreshold);
207 
208   is_histogram_valid =
209       (self->histogram[candidate_delay] >= histogram_threshold) &&
210       (self->candidate_hits > kMinRequiredHits);
211 
212   return is_histogram_valid;
213 }
214 
215 // Performs a robust validation of the |candidate_delay| estimated in
216 // WebRtc_ProcessBinarySpectrum().  The algorithm takes the
217 // |is_instantaneous_valid| and the |is_histogram_valid| and combines them
218 // into a robust validation.  The HistogramBasedValidation() has to be called
219 // prior to this call.
220 // For further description on how the combination is done, see commented code.
221 //
222 // Inputs:
223 //  - candidate_delay         : The delay to validate.
224 //  - is_instantaneous_valid  : The instantaneous validation performed in
225 //                              WebRtc_ProcessBinarySpectrum().
226 //  - is_histogram_valid      : The histogram based validation.
227 //
228 // Return value:
229 //  - is_robust               : 1 - The candidate_delay is valid according to a
230 //                                  combination of the two inputs.
231 //                            : 0 - Otherwise.
RobustValidation(const BinaryDelayEstimator * self,int candidate_delay,int is_instantaneous_valid,int is_histogram_valid)232 static int RobustValidation(const BinaryDelayEstimator* self,
233                             int candidate_delay,
234                             int is_instantaneous_valid,
235                             int is_histogram_valid) {
236   int is_robust = 0;
237 
238   // The final robust validation is based on the two algorithms; 1) the
239   // |is_instantaneous_valid| and 2) the histogram based with result stored in
240   // |is_histogram_valid|.
241   //   i) Before we actually have a valid estimate (|last_delay| == -2), we say
242   //      a candidate is valid if either algorithm states so
243   //      (|is_instantaneous_valid| OR |is_histogram_valid|).
244   is_robust = (self->last_delay < 0) &&
245       (is_instantaneous_valid || is_histogram_valid);
246   //  ii) Otherwise, we need both algorithms to be certain
247   //      (|is_instantaneous_valid| AND |is_histogram_valid|)
248   is_robust |= is_instantaneous_valid && is_histogram_valid;
249   // iii) With one exception, i.e., the histogram based algorithm can overrule
250   //      the instantaneous one if |is_histogram_valid| = 1 and the histogram
251   //      is significantly strong.
252   is_robust |= is_histogram_valid &&
253       (self->histogram[candidate_delay] > self->last_delay_histogram);
254 
255   return is_robust;
256 }
257 
WebRtc_FreeBinaryDelayEstimatorFarend(BinaryDelayEstimatorFarend * self)258 void WebRtc_FreeBinaryDelayEstimatorFarend(BinaryDelayEstimatorFarend* self) {
259 
260   if (self == NULL) {
261     return;
262   }
263 
264   free(self->binary_far_history);
265   self->binary_far_history = NULL;
266 
267   free(self->far_bit_counts);
268   self->far_bit_counts = NULL;
269 
270   free(self);
271 }
272 
WebRtc_CreateBinaryDelayEstimatorFarend(int history_size)273 BinaryDelayEstimatorFarend* WebRtc_CreateBinaryDelayEstimatorFarend(
274     int history_size) {
275   BinaryDelayEstimatorFarend* self = NULL;
276 
277   if (history_size > 1) {
278     // Sanity conditions fulfilled.
279     self = malloc(sizeof(BinaryDelayEstimatorFarend));
280   }
281   if (self == NULL) {
282     return NULL;
283   }
284 
285   self->history_size = 0;
286   self->binary_far_history = NULL;
287   self->far_bit_counts = NULL;
288   if (WebRtc_AllocateFarendBufferMemory(self, history_size) == 0) {
289     WebRtc_FreeBinaryDelayEstimatorFarend(self);
290     self = NULL;
291   }
292   return self;
293 }
294 
WebRtc_AllocateFarendBufferMemory(BinaryDelayEstimatorFarend * self,int history_size)295 int WebRtc_AllocateFarendBufferMemory(BinaryDelayEstimatorFarend* self,
296                                       int history_size) {
297   assert(self != NULL);
298   // (Re-)Allocate memory for history buffers.
299   self->binary_far_history =
300       realloc(self->binary_far_history,
301               history_size * sizeof(*self->binary_far_history));
302   self->far_bit_counts = realloc(self->far_bit_counts,
303                                  history_size * sizeof(*self->far_bit_counts));
304   if ((self->binary_far_history == NULL) || (self->far_bit_counts == NULL)) {
305     history_size = 0;
306   }
307   // Fill with zeros if we have expanded the buffers.
308   if (history_size > self->history_size) {
309     int size_diff = history_size - self->history_size;
310     memset(&self->binary_far_history[self->history_size],
311            0,
312            sizeof(*self->binary_far_history) * size_diff);
313     memset(&self->far_bit_counts[self->history_size],
314            0,
315            sizeof(*self->far_bit_counts) * size_diff);
316   }
317   self->history_size = history_size;
318 
319   return self->history_size;
320 }
321 
WebRtc_InitBinaryDelayEstimatorFarend(BinaryDelayEstimatorFarend * self)322 void WebRtc_InitBinaryDelayEstimatorFarend(BinaryDelayEstimatorFarend* self) {
323   assert(self != NULL);
324   memset(self->binary_far_history, 0, sizeof(uint32_t) * self->history_size);
325   memset(self->far_bit_counts, 0, sizeof(int) * self->history_size);
326 }
327 
WebRtc_SoftResetBinaryDelayEstimatorFarend(BinaryDelayEstimatorFarend * self,int delay_shift)328 void WebRtc_SoftResetBinaryDelayEstimatorFarend(
329     BinaryDelayEstimatorFarend* self, int delay_shift) {
330   int abs_shift = abs(delay_shift);
331   int shift_size = 0;
332   int dest_index = 0;
333   int src_index = 0;
334   int padding_index = 0;
335 
336   assert(self != NULL);
337   shift_size = self->history_size - abs_shift;
338   assert(shift_size > 0);
339   if (delay_shift == 0) {
340     return;
341   } else if (delay_shift > 0) {
342     dest_index = abs_shift;
343   } else if (delay_shift < 0) {
344     src_index = abs_shift;
345     padding_index = shift_size;
346   }
347 
348   // Shift and zero pad buffers.
349   memmove(&self->binary_far_history[dest_index],
350           &self->binary_far_history[src_index],
351           sizeof(*self->binary_far_history) * shift_size);
352   memset(&self->binary_far_history[padding_index], 0,
353          sizeof(*self->binary_far_history) * abs_shift);
354   memmove(&self->far_bit_counts[dest_index],
355           &self->far_bit_counts[src_index],
356           sizeof(*self->far_bit_counts) * shift_size);
357   memset(&self->far_bit_counts[padding_index], 0,
358          sizeof(*self->far_bit_counts) * abs_shift);
359 }
360 
WebRtc_AddBinaryFarSpectrum(BinaryDelayEstimatorFarend * handle,uint32_t binary_far_spectrum)361 void WebRtc_AddBinaryFarSpectrum(BinaryDelayEstimatorFarend* handle,
362                                  uint32_t binary_far_spectrum) {
363   assert(handle != NULL);
364   // Shift binary spectrum history and insert current |binary_far_spectrum|.
365   memmove(&(handle->binary_far_history[1]), &(handle->binary_far_history[0]),
366           (handle->history_size - 1) * sizeof(uint32_t));
367   handle->binary_far_history[0] = binary_far_spectrum;
368 
369   // Shift history of far-end binary spectrum bit counts and insert bit count
370   // of current |binary_far_spectrum|.
371   memmove(&(handle->far_bit_counts[1]), &(handle->far_bit_counts[0]),
372           (handle->history_size - 1) * sizeof(int));
373   handle->far_bit_counts[0] = BitCount(binary_far_spectrum);
374 }
375 
WebRtc_FreeBinaryDelayEstimator(BinaryDelayEstimator * self)376 void WebRtc_FreeBinaryDelayEstimator(BinaryDelayEstimator* self) {
377 
378   if (self == NULL) {
379     return;
380   }
381 
382   free(self->mean_bit_counts);
383   self->mean_bit_counts = NULL;
384 
385   free(self->bit_counts);
386   self->bit_counts = NULL;
387 
388   free(self->binary_near_history);
389   self->binary_near_history = NULL;
390 
391   free(self->histogram);
392   self->histogram = NULL;
393 
394   // BinaryDelayEstimator does not have ownership of |farend|, hence we do not
395   // free the memory here. That should be handled separately by the user.
396   self->farend = NULL;
397 
398   free(self);
399 }
400 
WebRtc_CreateBinaryDelayEstimator(BinaryDelayEstimatorFarend * farend,int max_lookahead)401 BinaryDelayEstimator* WebRtc_CreateBinaryDelayEstimator(
402     BinaryDelayEstimatorFarend* farend, int max_lookahead) {
403   BinaryDelayEstimator* self = NULL;
404 
405   if ((farend != NULL) && (max_lookahead >= 0)) {
406     // Sanity conditions fulfilled.
407     self = malloc(sizeof(BinaryDelayEstimator));
408   }
409   if (self == NULL) {
410     return NULL;
411   }
412 
413   self->farend = farend;
414   self->near_history_size = max_lookahead + 1;
415   self->history_size = 0;
416   self->robust_validation_enabled = 0;  // Disabled by default.
417   self->allowed_offset = 0;
418 
419   self->lookahead = max_lookahead;
420 
421   // Allocate memory for spectrum and history buffers.
422   self->mean_bit_counts = NULL;
423   self->bit_counts = NULL;
424   self->histogram = NULL;
425   self->binary_near_history =
426       malloc((max_lookahead + 1) * sizeof(*self->binary_near_history));
427   if (self->binary_near_history == NULL ||
428       WebRtc_AllocateHistoryBufferMemory(self, farend->history_size) == 0) {
429     WebRtc_FreeBinaryDelayEstimator(self);
430     self = NULL;
431   }
432 
433   return self;
434 }
435 
WebRtc_AllocateHistoryBufferMemory(BinaryDelayEstimator * self,int history_size)436 int WebRtc_AllocateHistoryBufferMemory(BinaryDelayEstimator* self,
437                                        int history_size) {
438   BinaryDelayEstimatorFarend* far = self->farend;
439   // (Re-)Allocate memory for spectrum and history buffers.
440   if (history_size != far->history_size) {
441     // Only update far-end buffers if we need.
442     history_size = WebRtc_AllocateFarendBufferMemory(far, history_size);
443   }
444   // The extra array element in |mean_bit_counts| and |histogram| is a dummy
445   // element only used while |last_delay| == -2, i.e., before we have a valid
446   // estimate.
447   self->mean_bit_counts =
448       realloc(self->mean_bit_counts,
449               (history_size + 1) * sizeof(*self->mean_bit_counts));
450   self->bit_counts =
451       realloc(self->bit_counts, history_size * sizeof(*self->bit_counts));
452   self->histogram =
453       realloc(self->histogram, (history_size + 1) * sizeof(*self->histogram));
454 
455   if ((self->mean_bit_counts == NULL) ||
456       (self->bit_counts == NULL) ||
457       (self->histogram == NULL)) {
458     history_size = 0;
459   }
460   // Fill with zeros if we have expanded the buffers.
461   if (history_size > self->history_size) {
462     int size_diff = history_size - self->history_size;
463     memset(&self->mean_bit_counts[self->history_size],
464            0,
465            sizeof(*self->mean_bit_counts) * size_diff);
466     memset(&self->bit_counts[self->history_size],
467            0,
468            sizeof(*self->bit_counts) * size_diff);
469     memset(&self->histogram[self->history_size],
470            0,
471            sizeof(*self->histogram) * size_diff);
472   }
473   self->history_size = history_size;
474 
475   return self->history_size;
476 }
477 
WebRtc_InitBinaryDelayEstimator(BinaryDelayEstimator * self)478 void WebRtc_InitBinaryDelayEstimator(BinaryDelayEstimator* self) {
479   int i = 0;
480   assert(self != NULL);
481 
482   memset(self->bit_counts, 0, sizeof(int32_t) * self->history_size);
483   memset(self->binary_near_history,
484          0,
485          sizeof(uint32_t) * self->near_history_size);
486   for (i = 0; i <= self->history_size; ++i) {
487     self->mean_bit_counts[i] = (20 << 9);  // 20 in Q9.
488     self->histogram[i] = 0.f;
489   }
490   self->minimum_probability = kMaxBitCountsQ9;  // 32 in Q9.
491   self->last_delay_probability = (int) kMaxBitCountsQ9;  // 32 in Q9.
492 
493   // Default return value if we're unable to estimate. -1 is used for errors.
494   self->last_delay = -2;
495 
496   self->last_candidate_delay = -2;
497   self->compare_delay = self->history_size;
498   self->candidate_hits = 0;
499   self->last_delay_histogram = 0.f;
500 }
501 
WebRtc_SoftResetBinaryDelayEstimator(BinaryDelayEstimator * self,int delay_shift)502 int WebRtc_SoftResetBinaryDelayEstimator(BinaryDelayEstimator* self,
503                                          int delay_shift) {
504   int lookahead = 0;
505   assert(self != NULL);
506   lookahead = self->lookahead;
507   self->lookahead -= delay_shift;
508   if (self->lookahead < 0) {
509     self->lookahead = 0;
510   }
511   if (self->lookahead > self->near_history_size - 1) {
512     self->lookahead = self->near_history_size - 1;
513   }
514   return lookahead - self->lookahead;
515 }
516 
WebRtc_ProcessBinarySpectrum(BinaryDelayEstimator * self,uint32_t binary_near_spectrum)517 int WebRtc_ProcessBinarySpectrum(BinaryDelayEstimator* self,
518                                  uint32_t binary_near_spectrum) {
519   int i = 0;
520   int candidate_delay = -1;
521   int valid_candidate = 0;
522 
523   int32_t value_best_candidate = kMaxBitCountsQ9;
524   int32_t value_worst_candidate = 0;
525   int32_t valley_depth = 0;
526 
527   assert(self != NULL);
528   if (self->farend->history_size != self->history_size) {
529     // Non matching history sizes.
530     return -1;
531   }
532   if (self->near_history_size > 1) {
533     // If we apply lookahead, shift near-end binary spectrum history. Insert
534     // current |binary_near_spectrum| and pull out the delayed one.
535     memmove(&(self->binary_near_history[1]), &(self->binary_near_history[0]),
536             (self->near_history_size - 1) * sizeof(uint32_t));
537     self->binary_near_history[0] = binary_near_spectrum;
538     binary_near_spectrum = self->binary_near_history[self->lookahead];
539   }
540 
541   // Compare with delayed spectra and store the |bit_counts| for each delay.
542   BitCountComparison(binary_near_spectrum, self->farend->binary_far_history,
543                      self->history_size, self->bit_counts);
544 
545   // Update |mean_bit_counts|, which is the smoothed version of |bit_counts|.
546   for (i = 0; i < self->history_size; i++) {
547     // |bit_counts| is constrained to [0, 32], meaning we can smooth with a
548     // factor up to 2^26. We use Q9.
549     int32_t bit_count = (self->bit_counts[i] << 9);  // Q9.
550 
551     // Update |mean_bit_counts| only when far-end signal has something to
552     // contribute. If |far_bit_counts| is zero the far-end signal is weak and
553     // we likely have a poor echo condition, hence don't update.
554     if (self->farend->far_bit_counts[i] > 0) {
555       // Make number of right shifts piecewise linear w.r.t. |far_bit_counts|.
556       int shifts = kShiftsAtZero;
557       shifts -= (kShiftsLinearSlope * self->farend->far_bit_counts[i]) >> 4;
558       WebRtc_MeanEstimatorFix(bit_count, shifts, &(self->mean_bit_counts[i]));
559     }
560   }
561 
562   // Find |candidate_delay|, |value_best_candidate| and |value_worst_candidate|
563   // of |mean_bit_counts|.
564   for (i = 0; i < self->history_size; i++) {
565     if (self->mean_bit_counts[i] < value_best_candidate) {
566       value_best_candidate = self->mean_bit_counts[i];
567       candidate_delay = i;
568     }
569     if (self->mean_bit_counts[i] > value_worst_candidate) {
570       value_worst_candidate = self->mean_bit_counts[i];
571     }
572   }
573   valley_depth = value_worst_candidate - value_best_candidate;
574 
575   // The |value_best_candidate| is a good indicator on the probability of
576   // |candidate_delay| being an accurate delay (a small |value_best_candidate|
577   // means a good binary match). In the following sections we make a decision
578   // whether to update |last_delay| or not.
579   // 1) If the difference bit counts between the best and the worst delay
580   //    candidates is too small we consider the situation to be unreliable and
581   //    don't update |last_delay|.
582   // 2) If the situation is reliable we update |last_delay| if the value of the
583   //    best candidate delay has a value less than
584   //     i) an adaptive threshold |minimum_probability|, or
585   //    ii) this corresponding value |last_delay_probability|, but updated at
586   //        this time instant.
587 
588   // Update |minimum_probability|.
589   if ((self->minimum_probability > kProbabilityLowerLimit) &&
590       (valley_depth > kProbabilityMinSpread)) {
591     // The "hard" threshold can't be lower than 17 (in Q9).
592     // The valley in the curve also has to be distinct, i.e., the
593     // difference between |value_worst_candidate| and |value_best_candidate| has
594     // to be large enough.
595     int32_t threshold = value_best_candidate + kProbabilityOffset;
596     if (threshold < kProbabilityLowerLimit) {
597       threshold = kProbabilityLowerLimit;
598     }
599     if (self->minimum_probability > threshold) {
600       self->minimum_probability = threshold;
601     }
602   }
603   // Update |last_delay_probability|.
604   // We use a Markov type model, i.e., a slowly increasing level over time.
605   self->last_delay_probability++;
606   // Validate |candidate_delay|.  We have a reliable instantaneous delay
607   // estimate if
608   //  1) The valley is distinct enough (|valley_depth| > |kProbabilityOffset|)
609   // and
610   //  2) The depth of the valley is deep enough
611   //      (|value_best_candidate| < |minimum_probability|)
612   //     and deeper than the best estimate so far
613   //      (|value_best_candidate| < |last_delay_probability|)
614   valid_candidate = ((valley_depth > kProbabilityOffset) &&
615       ((value_best_candidate < self->minimum_probability) ||
616           (value_best_candidate < self->last_delay_probability)));
617 
618   UpdateRobustValidationStatistics(self, candidate_delay, valley_depth,
619                                    value_best_candidate);
620   if (self->robust_validation_enabled) {
621     int is_histogram_valid = HistogramBasedValidation(self, candidate_delay);
622     valid_candidate = RobustValidation(self, candidate_delay, valid_candidate,
623                                        is_histogram_valid);
624 
625   }
626   if (valid_candidate) {
627     if (candidate_delay != self->last_delay) {
628       self->last_delay_histogram =
629           (self->histogram[candidate_delay] > kLastHistogramMax ?
630               kLastHistogramMax : self->histogram[candidate_delay]);
631       // Adjust the histogram if we made a change to |last_delay|, though it was
632       // not the most likely one according to the histogram.
633       if (self->histogram[candidate_delay] <
634           self->histogram[self->compare_delay]) {
635         self->histogram[self->compare_delay] = self->histogram[candidate_delay];
636       }
637     }
638     self->last_delay = candidate_delay;
639     if (value_best_candidate < self->last_delay_probability) {
640       self->last_delay_probability = value_best_candidate;
641     }
642     self->compare_delay = self->last_delay;
643   }
644 
645   return self->last_delay;
646 }
647 
WebRtc_binary_last_delay(BinaryDelayEstimator * self)648 int WebRtc_binary_last_delay(BinaryDelayEstimator* self) {
649   assert(self != NULL);
650   return self->last_delay;
651 }
652 
WebRtc_binary_last_delay_quality(BinaryDelayEstimator * self)653 float WebRtc_binary_last_delay_quality(BinaryDelayEstimator* self) {
654   float quality = 0;
655   assert(self != NULL);
656 
657   if (self->robust_validation_enabled) {
658     // Simply a linear function of the histogram height at delay estimate.
659     quality = self->histogram[self->compare_delay] / kHistogramMax;
660   } else {
661     // Note that |last_delay_probability| states how deep the minimum of the
662     // cost function is, so it is rather an error probability.
663     quality = (float) (kMaxBitCountsQ9 - self->last_delay_probability) /
664         kMaxBitCountsQ9;
665     if (quality < 0) {
666       quality = 0;
667     }
668   }
669   return quality;
670 }
671 
WebRtc_MeanEstimatorFix(int32_t new_value,int factor,int32_t * mean_value)672 void WebRtc_MeanEstimatorFix(int32_t new_value,
673                              int factor,
674                              int32_t* mean_value) {
675   int32_t diff = new_value - *mean_value;
676 
677   // mean_new = mean_value + ((new_value - mean_value) >> factor);
678   if (diff < 0) {
679     diff = -((-diff) >> factor);
680   } else {
681     diff = (diff >> factor);
682   }
683   *mean_value += diff;
684 }
685