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// Copyright (c) 2012 The Chromium Authors. All rights reserved.
// Use of this source code is governed by a BSD-style license that can be
// found in the LICENSE file.
#include "content/browser/speech/endpointer/energy_endpointer.h"
#include <math.h>
#include <stddef.h>
#include "base/logging.h"
#include "base/macros.h"
namespace {
// Returns the RMS (quadratic mean) of the input signal.
float RMS(const int16_t* samples, int num_samples) {
int64_t ssq_int64 = 0;
int64_t sum_int64 = 0;
for (int i = 0; i < num_samples; ++i) {
sum_int64 += samples[i];
ssq_int64 += samples[i] * samples[i];
}
// now convert to floats.
double sum = static_cast<double>(sum_int64);
sum /= num_samples;
double ssq = static_cast<double>(ssq_int64);
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 content {
// 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.
DISALLOW_COPY_AND_ASSIGN(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 received 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;
DVLOG(1) << "decision: forced to false, time: " << 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:
LOG(WARNING) << "Invalid case in switch: " << status_;
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);
DVLOG(1) << "FAST UPDATE, frame_counter_ " << frame_counter_
<< ", fast_update_frames_ " << 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 content