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Add a sparse FIR filter implementation

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A Finite Impulse Response filter implementation which takes advantage of sparse coefficients.
The coefficients are assumed to be uniformly distributed and have an initial offset.

BUG=webrtc:3146
R=andrew@webrtc.org, bjornv@webrtc.org, kwiberg@webrtc.org

Review URL: https://webrtc-codereview.appspot.com/49659004

Cr-Commit-Position: refs/heads/master@{#9002}
This commit is contained in:
Alejandro Luebs 2015-04-14 15:51:28 -07:00
parent e432800aeb
commit a9c0ae284c
6 changed files with 347 additions and 0 deletions
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2
webrtc/common_audio/BUILD.gn
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@ -85,6 +85,8 @@ source_set("common_audio") {
"signal_processing/splitting_filter.c",
"signal_processing/sqrt_of_one_minus_x_squared.c",
"signal_processing/vector_scaling_operations.c",
"sparse_fir_filter.cc",
"sparse_fir_filter.h",
"vad/include/vad.h",
"vad/include/webrtc_vad.h",
"vad/vad.cc",

3
webrtc/common_audio/common_audio.gyp
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@ -99,6 +99,8 @@
'signal_processing/splitting_filter.c',
'signal_processing/sqrt_of_one_minus_x_squared.c',
'signal_processing/vector_scaling_operations.c',
'sparse_fir_filter.cc',
'sparse_fir_filter.h',
'vad/include/vad.h',
'vad/include/webrtc_vad.h',
'vad/vad.cc',
@ -259,6 +261,7 @@
'ring_buffer_unittest.cc',
'signal_processing/real_fft_unittest.cc',
'signal_processing/signal_processing_unittest.cc',
'sparse_fir_filter_unittest.cc',
'vad/vad_core_unittest.cc',
'vad/vad_filterbank_unittest.cc',
'vad/vad_gmm_unittest.cc',

3
webrtc/common_audio/fir_filter_unittest.cc
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@ -16,6 +16,7 @@
#include "webrtc/base/scoped_ptr.h"
namespace webrtc {
namespace {
static const float kCoefficients[] = {0.2f, 0.3f, 0.5f, 0.7f, 0.11f};
static const size_t kCoefficientsLength = sizeof(kCoefficients) /
@ -34,6 +35,8 @@ void VerifyOutput(const float* expected_output,
length * sizeof(expected_output[0])));
}
} // namespace
TEST(FIRFilterTest, FilterAsIdentity) {
const float kCoefficients[] = {1.f, 0.f, 0.f, 0.f, 0.f};
float output[kInputLength];

60
webrtc/common_audio/sparse_fir_filter.cc Normal file
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@ -0,0 +1,60 @@
/*
* Copyright (c) 2015 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 "webrtc/common_audio/sparse_fir_filter.h"
#include "webrtc/base/checks.h"
namespace webrtc {
SparseFIRFilter::SparseFIRFilter(const float* nonzero_coeffs,
size_t num_nonzero_coeffs,
size_t sparsity,
size_t offset)
: sparsity_(sparsity),
offset_(offset),
nonzero_coeffs_(nonzero_coeffs, nonzero_coeffs + num_nonzero_coeffs),
state_(sparsity_ * (num_nonzero_coeffs - 1) + offset_, 0.f) {
CHECK_GE(num_nonzero_coeffs, 1u);
CHECK_GE(sparsity, 1u);
}
void SparseFIRFilter::Filter(const float* in, size_t length, float* out) {
// Convolves the input signal |in| with the filter kernel |nonzero_coeffs_|
// taking into account the previous state.
for (size_t i = 0; i < length; ++i) {
out[i] = 0.f;
size_t j;
for (j = 0; i >= j * sparsity_ + offset_ &&
j < nonzero_coeffs_.size(); ++j) {
out[i] += in[i - j * sparsity_ - offset_] * nonzero_coeffs_[j];
}
for (; j < nonzero_coeffs_.size(); ++j) {
out[i] += state_[i + (nonzero_coeffs_.size() - j - 1) * sparsity_] *
nonzero_coeffs_[j];
}
}
// Update current state.
if (state_.size() > 0u) {
if (length >= state_.size()) {
std::memcpy(&state_.front(),
&in[length - state_.size()],
state_.size() * sizeof(*in));
} else {
std::memmove(&state_.front(),
&state_[length],
(state_.size() - length) * sizeof(state_[0]));
std::memcpy(&state_[state_.size() - length], in, length * sizeof(*in));
}
}
}
} // namespace webrtc

48
webrtc/common_audio/sparse_fir_filter.h Normal file
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@ -0,0 +1,48 @@
/*
* Copyright (c) 2015 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.
*/
#ifndef WEBRTC_COMMON_AUDIO_SPARSE_FIR_FILTER_H_
#define WEBRTC_COMMON_AUDIO_SPARSE_FIR_FILTER_H_
#include <cstring>
#include <vector>
namespace webrtc {
// A Finite Impulse Response filter implementation which takes advantage of a
// sparse structure with uniformly distributed non-zero coefficients.
class SparseFIRFilter {
public:
// |num_nonzero_coeffs| is the number of non-zero coefficients,
// |nonzero_coeffs|. They are assumed to be uniformly distributed every
// |sparsity| samples and with an initial |offset|. The rest of the filter
// coefficients will be assumed zeros. For example, with sparsity = 3, and
// offset = 1 the filter coefficients will be:
// B = [0 coeffs[0] 0 0 coeffs[1] 0 0 coeffs[2] ... ]
// All initial state values will be zeros.
SparseFIRFilter(const float* nonzero_coeffs,
size_t num_nonzero_coeffs,
size_t sparsity,
size_t offset);
// Filters the |in| data supplied.
// |out| must be previously allocated and it must be at least of |length|.
void Filter(const float* in, size_t length, float* out);
private:
const size_t sparsity_;
const size_t offset_;
const std::vector<float> nonzero_coeffs_;
std::vector<float> state_;
};
} // namespace webrtc
#endif // WEBRTC_COMMON_AUDIO_SPARSE_FIR_FILTER_H_

231
webrtc/common_audio/sparse_fir_filter_unittest.cc Normal file
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@ -0,0 +1,231 @@
/*
* Copyright (c) 2015 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 "webrtc/common_audio/sparse_fir_filter.h"
#include "testing/gtest/include/gtest/gtest.h"
#include "webrtc/base/arraysize.h"
#include "webrtc/base/scoped_ptr.h"
#include "webrtc/common_audio/fir_filter.h"
namespace webrtc {
namespace {
static const float kCoeffs[] = {0.2f, 0.3f, 0.5f, 0.7f, 0.11f};
static const float kInput[] =
{1.f, 2.f, 3.f, 4.f, 5.f, 6.f, 7.f, 8.f, 9.f, 10.f};
template <size_t N>
void VerifyOutput(const float (&expected_output)[N], const float (&output)[N]) {
EXPECT_EQ(0, memcmp(expected_output, output, sizeof(output)));
}
} // namespace
TEST(SparseFIRFilterTest, FilterAsIdentity) {
const float kCoeff = 1.f;
const size_t kNumCoeff = 1;
const size_t kSparsity = 3;
const size_t kOffset = 0;
float output[arraysize(kInput)];
SparseFIRFilter filter(&kCoeff, kNumCoeff, kSparsity, kOffset);
filter.Filter(kInput, arraysize(kInput), output);
VerifyOutput(kInput, output);
}
TEST(SparseFIRFilterTest, SameOutputForScalarCoefficientAndDifferentSparsity) {
const float kCoeff = 2.f;
const size_t kNumCoeff = 1;
const size_t kLowSparsity = 1;
const size_t kHighSparsity = 7;
const size_t kOffset = 0;
float low_sparsity_output[arraysize(kInput)];
float high_sparsity_output[arraysize(kInput)];
SparseFIRFilter low_sparsity_filter(&kCoeff,
kNumCoeff,
kLowSparsity,
kOffset);
SparseFIRFilter high_sparsity_filter(&kCoeff,
kNumCoeff,
kHighSparsity,
kOffset);
low_sparsity_filter.Filter(kInput, arraysize(kInput), low_sparsity_output);
high_sparsity_filter.Filter(kInput, arraysize(kInput), high_sparsity_output);
VerifyOutput(low_sparsity_output, high_sparsity_output);
}
TEST(SparseFIRFilterTest, FilterUsedAsScalarMultiplication) {
const float kCoeff = 5.f;
const size_t kNumCoeff = 1;
const size_t kSparsity = 5;
const size_t kOffset = 0;
float output[arraysize(kInput)];
SparseFIRFilter filter(&kCoeff, kNumCoeff, kSparsity, kOffset);
filter.Filter(kInput, arraysize(kInput), output);
EXPECT_FLOAT_EQ(5.f, output[0]);
EXPECT_FLOAT_EQ(20.f, output[3]);
EXPECT_FLOAT_EQ(25.f, output[4]);
EXPECT_FLOAT_EQ(50.f, output[arraysize(kInput) - 1]);
}
TEST(SparseFIRFilterTest, FilterUsedAsInputShifting) {
const float kCoeff = 1.f;
const size_t kNumCoeff = 1;
const size_t kSparsity = 1;
const size_t kOffset = 4;
float output[arraysize(kInput)];
SparseFIRFilter filter(&kCoeff, kNumCoeff, kSparsity, kOffset);
filter.Filter(kInput, arraysize(kInput), output);
EXPECT_FLOAT_EQ(0.f, output[0]);
EXPECT_FLOAT_EQ(0.f, output[3]);
EXPECT_FLOAT_EQ(1.f, output[4]);
EXPECT_FLOAT_EQ(2.f, output[5]);
EXPECT_FLOAT_EQ(6.f, output[arraysize(kInput) - 1]);
}
TEST(SparseFIRFilterTest, FilterUsedAsArbitraryWeighting) {
const size_t kSparsity = 2;
const size_t kOffset = 1;
float output[arraysize(kInput)];
SparseFIRFilter filter(kCoeffs, arraysize(kCoeffs), kSparsity, kOffset);
filter.Filter(kInput, arraysize(kInput), output);
EXPECT_FLOAT_EQ(0.f, output[0]);
EXPECT_FLOAT_EQ(0.9f, output[3]);
EXPECT_FLOAT_EQ(1.4f, output[4]);
EXPECT_FLOAT_EQ(2.4f, output[5]);
EXPECT_FLOAT_EQ(8.61f, output[arraysize(kInput) - 1]);
}
TEST(SparseFIRFilterTest, FilterInLengthLesserOrEqualToCoefficientsLength) {
const size_t kSparsity = 1;
const size_t kOffset = 0;
float output[arraysize(kInput)];
SparseFIRFilter filter(kCoeffs, arraysize(kCoeffs), kSparsity, kOffset);
filter.Filter(kInput, 2, output);
EXPECT_FLOAT_EQ(0.2f, output[0]);
EXPECT_FLOAT_EQ(0.7f, output[1]);
}
TEST(SparseFIRFilterTest, MultipleFilterCalls) {
const size_t kSparsity = 1;
const size_t kOffset = 0;
float output[arraysize(kInput)];
SparseFIRFilter filter(kCoeffs, arraysize(kCoeffs), kSparsity, kOffset);
filter.Filter(kInput, 2, output);
EXPECT_FLOAT_EQ(0.2f, output[0]);
EXPECT_FLOAT_EQ(0.7f, output[1]);
filter.Filter(kInput, 2, output);
EXPECT_FLOAT_EQ(1.3f, output[0]);
EXPECT_FLOAT_EQ(2.4f, output[1]);
filter.Filter(kInput, 2, output);
EXPECT_FLOAT_EQ(2.81f, output[0]);
EXPECT_FLOAT_EQ(2.62f, output[1]);
filter.Filter(kInput, 2, output);
EXPECT_FLOAT_EQ(2.81f, output[0]);
EXPECT_FLOAT_EQ(2.62f, output[1]);
filter.Filter(&kInput[3], 3, output);
EXPECT_FLOAT_EQ(3.41f, output[0]);
EXPECT_FLOAT_EQ(4.12f, output[1]);
EXPECT_FLOAT_EQ(6.21f, output[2]);
filter.Filter(&kInput[3], 3, output);
EXPECT_FLOAT_EQ(8.12f, output[0]);
EXPECT_FLOAT_EQ(9.14f, output[1]);
EXPECT_FLOAT_EQ(9.45f, output[2]);
}
TEST(SparseFIRFilterTest, VerifySampleBasedVsBlockBasedFiltering) {
const size_t kSparsity = 3;
const size_t kOffset = 1;
float output_block_based[arraysize(kInput)];
SparseFIRFilter filter_block(kCoeffs,
arraysize(kCoeffs),
kSparsity,
kOffset);
filter_block.Filter(kInput, arraysize(kInput), output_block_based);
float output_sample_based[arraysize(kInput)];
SparseFIRFilter filter_sample(kCoeffs,
arraysize(kCoeffs),
kSparsity,
kOffset);
for (size_t i = 0; i < arraysize(kInput); ++i)
filter_sample.Filter(&kInput[i], 1, &output_sample_based[i]);
VerifyOutput(output_block_based, output_sample_based);
}
TEST(SparseFIRFilterTest, SimpleHighPassFilter) {
const size_t kSparsity = 2;
const size_t kOffset = 2;
const float kHPCoeffs[] = {1.f, -1.f};
const float kConstantInput[] =
{1.f, 1.f, 1.f, 1.f, 1.f, 1.f, 1.f, 1.f, 1.f, 1.f};
float output[arraysize(kConstantInput)];
SparseFIRFilter filter(kHPCoeffs, arraysize(kHPCoeffs), kSparsity, kOffset);
filter.Filter(kConstantInput, arraysize(kConstantInput), output);
EXPECT_FLOAT_EQ(0.f, output[0]);
EXPECT_FLOAT_EQ(0.f, output[1]);
EXPECT_FLOAT_EQ(1.f, output[2]);
EXPECT_FLOAT_EQ(1.f, output[3]);
for (size_t i = kSparsity + kOffset; i < arraysize(kConstantInput); ++i)
EXPECT_FLOAT_EQ(0.f, output[i]);
}
TEST(SparseFIRFilterTest, SimpleLowPassFilter) {
const size_t kSparsity = 2;
const size_t kOffset = 2;
const float kLPCoeffs[] = {1.f, 1.f};
const float kHighFrequencyInput[] =
{1.f, 1.f, -1.f, -1.f, 1.f, 1.f, -1.f, -1.f, 1.f, 1.f};
float output[arraysize(kHighFrequencyInput)];
SparseFIRFilter filter(kLPCoeffs, arraysize(kLPCoeffs), kSparsity, kOffset);
filter.Filter(kHighFrequencyInput, arraysize(kHighFrequencyInput), output);
EXPECT_FLOAT_EQ(0.f, output[0]);
EXPECT_FLOAT_EQ(0.f, output[1]);
EXPECT_FLOAT_EQ(1.f, output[2]);
EXPECT_FLOAT_EQ(1.f, output[3]);
for (size_t i = kSparsity + kOffset; i < arraysize(kHighFrequencyInput); ++i)
EXPECT_FLOAT_EQ(0.f, output[i]);
}
TEST(SparseFIRFilterTest, SameOutputWhenSwappedCoefficientsAndInput) {
const size_t kSparsity = 1;
const size_t kOffset = 0;
float output[arraysize(kCoeffs)];
float output_swapped[arraysize(kCoeffs)];
SparseFIRFilter filter(kCoeffs, arraysize(kCoeffs), kSparsity, kOffset);
// Use arraysize(kCoeffs) for in_length to get same-length outputs.
filter.Filter(kInput, arraysize(kCoeffs), output);
SparseFIRFilter filter_swapped(kInput,
arraysize(kCoeffs),
kSparsity,
kOffset);
filter_swapped.Filter(kCoeffs, arraysize(kCoeffs), output_swapped);
VerifyOutput(output, output_swapped);
}
TEST(SparseFIRFilterTest, SameOutputAsFIRFilterWhenSparsityOneAndOffsetZero) {
const size_t kSparsity = 1;
const size_t kOffset = 0;
float output[arraysize(kInput)];
float sparse_output[arraysize(kInput)];
rtc::scoped_ptr<FIRFilter> filter(FIRFilter::Create(kCoeffs,
arraysize(kCoeffs),
arraysize(kInput)));
SparseFIRFilter sparse_filter(kCoeffs,
arraysize(kCoeffs),
kSparsity,
kOffset);
filter->Filter(kInput, arraysize(kInput), output);
sparse_filter.Filter(kInput, arraysize(kInput), sparse_output);
for (size_t i = 0; i < arraysize(kInput); ++i) {
EXPECT_FLOAT_EQ(output[i], sparse_output[i]);
}
}
} // namespace webrtc