tor-browser

energy_endpointer.cc (14011B)

---

// Copyright (c) 2013 The Chromium Authors. All rights reserved.
//
// Redistribution and use in source and binary forms, with or without
// modification, are permitted provided that the following conditions are
// met:
//
//    * Redistributions of source code must retain the above copyright
// notice, this list of conditions and the following disclaimer.
//    * Redistributions in binary form must reproduce the above
// copyright notice, this list of conditions and the following disclaimer
// in the documentation and/or other materials provided with the
// distribution.
//    * Neither the name of Google Inc. nor the names of its
// contributors may be used to endorse or promote products derived from
// this software without specific prior written permission.
//
// THIS SOFTWARE IS PROVIDED BY THE COPYRIGHT HOLDERS AND CONTRIBUTORS
// "AS IS" AND ANY EXPRESS OR IMPLIED WARRANTIES, INCLUDING, BUT NOT
// LIMITED TO, THE IMPLIED WARRANTIES OF MERCHANTABILITY AND FITNESS FOR
// A PARTICULAR PURPOSE ARE DISCLAIMED. IN NO EVENT SHALL THE COPYRIGHT
// OWNER OR CONTRIBUTORS BE LIABLE FOR ANY DIRECT, INDIRECT, INCIDENTAL,
// SPECIAL, EXEMPLARY, OR CONSEQUENTIAL DAMAGES (INCLUDING, BUT NOT
// LIMITED TO, PROCUREMENT OF SUBSTITUTE GOODS OR SERVICES; LOSS OF USE,
// DATA, OR PROFITS; OR BUSINESS INTERRUPTION) HOWEVER CAUSED AND ON ANY
// THEORY OF LIABILITY, WHETHER IN CONTRACT, STRICT LIABILITY, OR TORT
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// OF THIS SOFTWARE, EVEN IF ADVISED OF THE POSSIBILITY OF SUCH DAMAGE.

#include "energy_endpointer.h"

#include <math.h>

namespace {

// Returns the RMS (quadratic mean) of the input signal.
float RMS(const int16_t* samples, int num_samples) {
 int64_t ssq_int64_t = 0;
 int64_t sum_int64_t = 0;
 for (int i = 0; i < num_samples; ++i) {
   sum_int64_t += samples[i];
   ssq_int64_t += samples[i] * samples[i];
 }
 // now convert to floats.
 double sum = static_cast<double>(sum_int64_t);
 sum /= num_samples;
 double ssq = static_cast<double>(ssq_int64_t);
 return static_cast<float>(sqrt((ssq / num_samples) - (sum * sum)));
}

int64_t Secs2Usecs(float seconds) {
 return static_cast<int64_t>(0.5 + (1.0e6 * seconds));
}

float GetDecibel(float value) {
 if (value > 1.0e-100)
   return 20 * log10(value);
 return -2000.0;
}

}  // namespace

namespace mozilla {

// Stores threshold-crossing histories for making decisions about the speech
// state.
class EnergyEndpointer::HistoryRing {
public:
 HistoryRing() : insertion_index_(0) {}

 // Resets the ring to |size| elements each with state |initial_state|
 void SetRing(int size, bool initial_state);

 // Inserts a new entry into the ring and drops the oldest entry.
 void Insert(int64_t time_us, bool decision);

 // Returns the time in microseconds of the most recently added entry.
 int64_t EndTime() const;

 // Returns the sum of all intervals during which 'decision' is true within
 // the time in seconds specified by 'duration'. The returned interval is
 // in seconds.
 float RingSum(float duration_sec);

private:
 struct DecisionPoint {
   int64_t time_us;
   bool decision;
 };

 std::vector<DecisionPoint> decision_points_;
 int insertion_index_;  // Index at which the next item gets added/inserted.

 HistoryRing(const HistoryRing&);
 void operator=(const HistoryRing&);
};

void EnergyEndpointer::HistoryRing::SetRing(int size, bool initial_state) {
 insertion_index_ = 0;
 decision_points_.clear();
 DecisionPoint init = { -1, initial_state };
 decision_points_.resize(size, init);
}

void EnergyEndpointer::HistoryRing::Insert(int64_t time_us, bool decision) {
 decision_points_[insertion_index_].time_us = time_us;
 decision_points_[insertion_index_].decision = decision;
 insertion_index_ = (insertion_index_ + 1) % decision_points_.size();
}

int64_t EnergyEndpointer::HistoryRing::EndTime() const {
 int ind = insertion_index_ - 1;
 if (ind < 0)
   ind = decision_points_.size() - 1;
 return decision_points_[ind].time_us;
}

float EnergyEndpointer::HistoryRing::RingSum(float duration_sec) {
 if (decision_points_.empty())
   return 0.0;

 int64_t sum_us = 0;
 int ind = insertion_index_ - 1;
 if (ind < 0)
   ind = decision_points_.size() - 1;
 int64_t end_us = decision_points_[ind].time_us;
 bool is_on = decision_points_[ind].decision;
 int64_t start_us = end_us - static_cast<int64_t>(0.5 + (1.0e6 * duration_sec));
 if (start_us < 0)
   start_us = 0;
 size_t n_summed = 1;  // n points ==> (n-1) intervals
 while ((decision_points_[ind].time_us > start_us) &&
        (n_summed < decision_points_.size())) {
   --ind;
   if (ind < 0)
     ind = decision_points_.size() - 1;
   if (is_on)
     sum_us += end_us - decision_points_[ind].time_us;
   is_on = decision_points_[ind].decision;
   end_us = decision_points_[ind].time_us;
   n_summed++;
 }

 return 1.0e-6f * sum_us;  //  Returns total time that was super threshold.
}

EnergyEndpointer::EnergyEndpointer()
   : status_(EP_PRE_SPEECH),
     offset_confirm_dur_sec_(0),
     endpointer_time_us_(0),
     fast_update_frames_(0),
     frame_counter_(0),
     max_window_dur_(4.0),
     sample_rate_(0),
     history_(new HistoryRing()),
     decision_threshold_(0),
     estimating_environment_(false),
     noise_level_(0),
     rms_adapt_(0),
     start_lag_(0),
     end_lag_(0),
     user_input_start_time_us_(0) {
}

EnergyEndpointer::~EnergyEndpointer() {
}

int EnergyEndpointer::TimeToFrame(float time) const {
 return static_cast<int32_t>(0.5 + (time / params_.frame_period()));
}

void EnergyEndpointer::Restart(bool reset_threshold) {
 status_ = EP_PRE_SPEECH;
 user_input_start_time_us_ = 0;

 if (reset_threshold) {
   decision_threshold_ = params_.decision_threshold();
   rms_adapt_ = decision_threshold_;
   noise_level_ = params_.decision_threshold() / 2.0f;
   frame_counter_ = 0;  // Used for rapid initial update of levels.
 }

 // Set up the memories to hold the history windows.
 history_->SetRing(TimeToFrame(max_window_dur_), false);

 // Flag that indicates that current input should be used for
 // estimating the environment. The user has not yet started input
 // by e.g. pressed the push-to-talk button. By default, this is
 // false for backward compatibility.
 estimating_environment_ = false;
}

void EnergyEndpointer::Init(const EnergyEndpointerParams& params) {
 params_ = params;

 // Find the longest history interval to be used, and make the ring
 // large enough to accommodate that number of frames.  NOTE: This
 // depends upon ep_frame_period being set correctly in the factory
 // that did this instantiation.
 max_window_dur_ = params_.onset_window();
 if (params_.speech_on_window() > max_window_dur_)
   max_window_dur_ = params_.speech_on_window();
 if (params_.offset_window() > max_window_dur_)
   max_window_dur_ = params_.offset_window();
 Restart(true);

 offset_confirm_dur_sec_ = params_.offset_window() -
                           params_.offset_confirm_dur();
 if (offset_confirm_dur_sec_ < 0.0)
   offset_confirm_dur_sec_ = 0.0;

 user_input_start_time_us_ = 0;

 // Flag that indicates that  current input should be used for
 // estimating the environment. The user has not yet started input
 // by e.g. pressed the push-to-talk button. By default, this is
 // false for backward compatibility.
 estimating_environment_ = false;
 // The initial value of the noise and speech levels is inconsequential.
 // The level of the first frame will overwrite these values.
 noise_level_ = params_.decision_threshold() / 2.0f;
 fast_update_frames_ =
     static_cast<int64_t>(params_.fast_update_dur() / params_.frame_period());

 frame_counter_ = 0;  // Used for rapid initial update of levels.

 sample_rate_ = params_.sample_rate();
 start_lag_ = static_cast<int>(sample_rate_ /
                               params_.max_fundamental_frequency());
 end_lag_ = static_cast<int>(sample_rate_ /
                             params_.min_fundamental_frequency());
}

void EnergyEndpointer::StartSession() {
 Restart(true);
}

void EnergyEndpointer::EndSession() {
 status_ = EP_POST_SPEECH;
}

void EnergyEndpointer::SetEnvironmentEstimationMode() {
 Restart(true);
 estimating_environment_ = true;
}

void EnergyEndpointer::SetUserInputMode() {
 estimating_environment_ = false;
 user_input_start_time_us_ = endpointer_time_us_;
}

void EnergyEndpointer::ProcessAudioFrame(int64_t time_us,
                                        const int16_t* samples,
                                        int num_samples,
                                        float* rms_out) {
 endpointer_time_us_ = time_us;
 float rms = RMS(samples, num_samples);

 // Check that this is user input audio vs. pre-input adaptation audio.
 // Input audio starts when the user indicates start of input, by e.g.
 // pressing push-to-talk. Audio recieved prior to that is used to update
 // noise and speech level estimates.
 if (!estimating_environment_) {
   bool decision = false;
   if ((endpointer_time_us_ - user_input_start_time_us_) <
       Secs2Usecs(params_.contamination_rejection_period())) {
     decision = false;
     //PR_LOG(GetSpeechRecognitionLog(), PR_LOG_DEBUG, ("decision: forced to false, time: %d", endpointer_time_us_));
   } else {
     decision = (rms > decision_threshold_);
   }

   history_->Insert(endpointer_time_us_, decision);

   switch (status_) {
     case EP_PRE_SPEECH:
       if (history_->RingSum(params_.onset_window()) >
           params_.onset_detect_dur()) {
         status_ = EP_POSSIBLE_ONSET;
       }
       break;

     case EP_POSSIBLE_ONSET: {
       float tsum = history_->RingSum(params_.onset_window());
       if (tsum > params_.onset_confirm_dur()) {
         status_ = EP_SPEECH_PRESENT;
       } else {  // If signal is not maintained, drop back to pre-speech.
         if (tsum <= params_.onset_detect_dur())
           status_ = EP_PRE_SPEECH;
       }
       break;
     }

     case EP_SPEECH_PRESENT: {
       // To induce hysteresis in the state residency, we allow a
       // smaller residency time in the on_ring, than was required to
       // enter the SPEECH_PERSENT state.
       float on_time = history_->RingSum(params_.speech_on_window());
       if (on_time < params_.on_maintain_dur())
         status_ = EP_POSSIBLE_OFFSET;
       break;
     }

     case EP_POSSIBLE_OFFSET:
       if (history_->RingSum(params_.offset_window()) <=
           offset_confirm_dur_sec_) {
         // Note that this offset time may be beyond the end
         // of the input buffer in a real-time system.  It will be up
         // to the RecognizerSession to decide what to do.
         status_ = EP_PRE_SPEECH;  // Automatically reset for next utterance.
       } else {  // If speech picks up again we allow return to SPEECH_PRESENT.
         if (history_->RingSum(params_.speech_on_window()) >=
             params_.on_maintain_dur())
           status_ = EP_SPEECH_PRESENT;
       }
       break;

     default:
       break;
   }

   // If this is a quiet, non-speech region, slowly adapt the detection
   // threshold to be about 6dB above the average RMS.
   if ((!decision) && (status_ == EP_PRE_SPEECH)) {
     decision_threshold_ = (0.98f * decision_threshold_) + (0.02f * 2 * rms);
     rms_adapt_ = decision_threshold_;
   } else {
     // If this is in a speech region, adapt the decision threshold to
     // be about 10dB below the average RMS. If the noise level is high,
     // the threshold is pushed up.
     // Adaptation up to a higher level is 5 times faster than decay to
     // a lower level.
     if ((status_ == EP_SPEECH_PRESENT) && decision) {
       if (rms_adapt_ > rms) {
         rms_adapt_ = (0.99f * rms_adapt_) + (0.01f * rms);
       } else {
         rms_adapt_ = (0.95f * rms_adapt_) + (0.05f * rms);
       }
       float target_threshold = 0.3f * rms_adapt_ +  noise_level_;
       decision_threshold_ = (.90f * decision_threshold_) +
                             (0.10f * target_threshold);
     }
   }

   // Set a floor
   if (decision_threshold_ < params_.min_decision_threshold())
     decision_threshold_ = params_.min_decision_threshold();
 }

 // Update speech and noise levels.
 UpdateLevels(rms);
 ++frame_counter_;

 if (rms_out)
   *rms_out = GetDecibel(rms);
}

float EnergyEndpointer::GetNoiseLevelDb() const {
 return GetDecibel(noise_level_);
}

void EnergyEndpointer::UpdateLevels(float rms) {
 // Update quickly initially. We assume this is noise and that
 // speech is 6dB above the noise.
 if (frame_counter_ < fast_update_frames_) {
   // Alpha increases from 0 to (k-1)/k where k is the number of time
   // steps in the initial adaptation period.
   float alpha = static_cast<float>(frame_counter_) /
       static_cast<float>(fast_update_frames_);
   noise_level_ = (alpha * noise_level_) + ((1 - alpha) * rms);
   //PR_LOG(GetSpeechRecognitionLog(), PR_LOG_DEBUG, ("FAST UPDATE, frame_counter_ %d, fast_update_frames_ %d", frame_counter_, fast_update_frames_));
 } else {
   // Update Noise level. The noise level adapts quickly downward, but
   // slowly upward. The noise_level_ parameter is not currently used
   // for threshold adaptation. It is used for UI feedback.
   if (noise_level_ < rms)
     noise_level_ = (0.999f * noise_level_) + (0.001f * rms);
   else
     noise_level_ = (0.95f * noise_level_) + (0.05f * rms);
 }
 if (estimating_environment_ || (frame_counter_ < fast_update_frames_)) {
   decision_threshold_ = noise_level_ * 2; // 6dB above noise level.
   // Set a floor
   if (decision_threshold_ < params_.min_decision_threshold())
     decision_threshold_ = params_.min_decision_threshold();
 }
}

EpStatus EnergyEndpointer::Status(int64_t* status_time)  const {
 *status_time = history_->EndTime();
 return status_;
}

}  // namespace mozilla