Opensource ML embedded evaluation kit
Change-Id: I12e807f19f5cacad7cef82572b6dd48252fd61fd
diff --git a/tests/use_case/asr/AsrFeaturesTests.cc b/tests/use_case/asr/AsrFeaturesTests.cc
new file mode 100644
index 0000000..9401f40
--- /dev/null
+++ b/tests/use_case/asr/AsrFeaturesTests.cc
@@ -0,0 +1,188 @@
+/*
+ * Copyright (c) 2021 Arm Limited. All rights reserved.
+ * SPDX-License-Identifier: Apache-2.0
+ *
+ * Licensed under the Apache License, Version 2.0 (the "License");
+ * you may not use this file except in compliance with the License.
+ * You may obtain a copy of the License at
+ *
+ * http://www.apache.org/licenses/LICENSE-2.0
+ *
+ * Unless required by applicable law or agreed to in writing, software
+ * distributed under the License is distributed on an "AS IS" BASIS,
+ * WITHOUT WARRANTIES OR CONDITIONS OF ANY KIND, either express or implied.
+ * See the License for the specific language governing permissions and
+ * limitations under the License.
+ */
+#include "DataStructures.hpp"
+#include "AsrGoldenFeatures.hpp"
+#include "hal.h"
+#include "TensorFlowLiteMicro.hpp"
+#include "Wav2LetterPreprocess.hpp"
+
+#include <catch.hpp>
+#include <random>
+
+class TestPreprocess : public arm::app::audio::asr::Preprocess {
+public:
+ TestPreprocess()
+ : arm::app::audio::asr::Preprocess(0,0,0,0)
+ {}
+
+ bool ComputeDeltas(arm::app::Array2d<float>& mfcc,
+ arm::app::Array2d<float>& delta1,
+ arm::app::Array2d<float>& delta2)
+ {
+ return this->_ComputeDeltas(mfcc, delta1, delta2);
+ }
+
+ float GetMean(arm::app::Array2d<float>& vec)
+ {
+ return this->_GetMean(vec);
+ }
+
+ float GetStdDev(arm::app::Array2d<float>& vec, const float mean)
+ {
+ return this->_GetStdDev(vec, mean);
+ }
+
+ void NormaliseVec(arm::app::Array2d<float>& vec)
+ {
+ return this->_NormaliseVec(vec);
+ }
+};
+
+template<class T>
+void CheckOutputs(const std::vector<T> goldenOutput, std::vector<T> output)
+{
+ const size_t goldenSize = goldenOutput.size();
+ const size_t realSize = output.size();
+
+ REQUIRE(realSize == goldenSize);
+ REQUIRE_THAT(output, Catch::Approx( goldenOutput ).margin(0.0001));
+}
+template void CheckOutputs<float>(const std::vector<float> goldenOutput, std::vector<float> output);
+
+void populateBuffer(const float* input, size_t size, size_t numMfccFeats, std::vector<std::vector<float>>& buf)
+{
+ size_t time = 0;
+ for (size_t i = 0; i < size; ++i) {
+ if (i > 0 && i % numMfccFeats == 0) {
+ ++time;
+ }
+ float featureValue = *(input + i);
+ buf[i % numMfccFeats][time] = featureValue;
+ }
+}
+
+void populateArray2dWithVectorOfVector(std::vector<std::vector<float>> vec, arm::app::Array2d<float>& buf)
+{
+ for (size_t i = 0; i < vec.size(); ++i) {
+ for (size_t j = 0; j < vec[i].size(); ++j) {
+ buf(i, j) = vec[i][j];
+ }
+ }
+}
+
+TEST_CASE("Floating point asr features calculation", "[ASR]")
+{
+ TestPreprocess tp;
+
+ SECTION("First and second diff")
+ {
+ constexpr uint32_t numMfccFeats = 13;
+ constexpr uint32_t numFeatVectors = 296;
+
+ arm::app::Array2d<float> mfccBuf(numMfccFeats, numFeatVectors);
+ arm::app::Array2d<float> delta1Buf(numMfccFeats, numFeatVectors);
+ arm::app::Array2d<float> delta2Buf(numMfccFeats, numFeatVectors);
+
+ std::vector<std::vector<float>> goldenMfccBuf(numMfccFeats, std::vector<float>(numFeatVectors));
+ std::vector<std::vector<float>> goldenDelta1Buf(numMfccFeats, std::vector<float>(numFeatVectors));
+ std::vector<std::vector<float>> goldenDelta2Buf(numMfccFeats, std::vector<float>(numFeatVectors));
+
+ populateBuffer(golden_asr_mfcc, golden_asr_mfcc_len, numMfccFeats, goldenMfccBuf);
+ populateBuffer(golden_diff1_features, golden_diff1_len, numMfccFeats, goldenDelta1Buf);
+ populateBuffer(golden_diff2_features, golden_diff2_len, numMfccFeats, goldenDelta2Buf);
+
+ populateArray2dWithVectorOfVector(goldenMfccBuf, mfccBuf);
+ std::fill(delta1Buf.begin(), delta1Buf.end(), 0.f);
+ std::fill(delta2Buf.begin(), delta2Buf.end(), 0.f);
+
+ tp.ComputeDeltas(mfccBuf, delta1Buf, delta2Buf);
+
+ /* First 4 and last 4 values are different because we pad AFTER diff calculated. */
+ for (size_t i = 0; i < numMfccFeats; ++i) {
+ const float* start_goldenDelta1Buf = goldenDelta1Buf[i].data() + 4;
+ const float* start_delta1 = delta1Buf.begin() + i * delta1Buf.size(1) + 4;
+ std::vector<float> goldenDataDelta1(start_goldenDelta1Buf, start_goldenDelta1Buf + numFeatVectors - 8);
+ std::vector<float> tensorDataDelta1(start_delta1, start_delta1 + numFeatVectors - 8);
+
+ CheckOutputs<float>(goldenDataDelta1,tensorDataDelta1);
+
+ const float* start_goldenDelta2Buf = goldenDelta2Buf[i].data() + 4;
+ const float* start_delta2 = delta2Buf.begin() + i * delta2Buf.size(1) + 4;
+ std::vector<float> goldenDataDelta2(start_goldenDelta2Buf, start_goldenDelta2Buf + numFeatVectors - 8);
+ std::vector<float> tensorDataDelta2(start_delta2, start_delta2 + numFeatVectors - 8);
+
+ CheckOutputs<float>(goldenDataDelta2,tensorDataDelta2);
+ }
+
+ }
+
+ SECTION("Mean")
+ {
+ std::vector<std::vector<float>> mean1vec{{1, 2},
+ {-1, -2}};
+ arm::app::Array2d<float> mean1(2,2); /* {{1, 2},{-1, -2}} */
+ populateArray2dWithVectorOfVector(mean1vec, mean1);
+ REQUIRE(0 == Approx(tp.GetMean(mean1)));
+
+ arm::app::Array2d<float> mean2(2, 2);
+ std::fill(mean2.begin(), mean2.end(), 0.f);
+ REQUIRE(0 == Approx(tp.GetMean(mean2)));
+
+ arm::app::Array2d<float> mean3(3,3);
+ std::fill(mean3.begin(), mean3.end(), 1.f);
+ REQUIRE(1 == Approx(tp.GetMean(mean3)));
+ }
+
+ SECTION("Std")
+ {
+ arm::app::Array2d<float> std1(2, 2);
+ std::fill(std1.begin(), std1.end(), 0.f); /* {{0, 0}, {0, 0}} */
+ REQUIRE(0 == Approx(tp.GetStdDev(std1, 0)));
+
+ std::vector<std::vector<float>> std2vec{{1, 2, 3, 4, 5}, {6, 7, 8, 9, 0}};
+ arm::app::Array2d<float> std2(2,5);
+ populateArray2dWithVectorOfVector(std2vec, std2);
+ const float mean = tp.GetMean(std2);
+ REQUIRE(2.872281323 == Approx(tp.GetStdDev(std2, mean)));
+
+ arm::app::Array2d<float> std3(2,2);
+ std::fill(std3.begin(), std3.end(), 1.f); /* std3{{1, 1}, {1, 1}}; */
+ REQUIRE(0 == Approx(tp.GetStdDev(std3, 1)));
+ }
+
+ SECTION("Norm") {
+ auto checker = [&](arm::app::Array2d<float>& d, std::vector<float>& g) {
+ tp.NormaliseVec(d);
+ std::vector<float> d_vec(d.begin(), d.end());
+ REQUIRE_THAT(g, Catch::Approx(d_vec));
+ };
+
+ std::vector<std::vector<float>> norm0vec{{1, 1}, {1, 1}};
+ std::vector<float> goldenNorm0 {0, 0, 0, 0};
+ arm::app::Array2d<float> norm0(2, 2);
+ populateArray2dWithVectorOfVector(norm0vec, norm0);
+ checker(norm0, goldenNorm0);
+
+ std::vector<std::vector<float>> norm1vec{{1, 2, 3, 4, 5}, {6, 7, 8, 9, 0}};
+ std::vector<float> goldenNorm1 {
+ -1.218543592, -0.87038828, -0.522232968, -0.174077656, 0.174077656,
+ 0.522232968, 0.87038828, 1.218543592, 1.566698904, -1.566698904};
+ arm::app::Array2d<float> norm1(2, 5);
+ populateArray2dWithVectorOfVector(norm1vec, norm1);
+ checker(norm1, goldenNorm1);
+ }
+}