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RNN VAD: unit tests for RnnBasedVad

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Bug: webrtc:10480
Change-Id: I4ac8ae044261f94db7a1e9559aa61f532602b408
Reviewed-on: https://webrtc-review.googlesource.com/c/src/+/195446
Commit-Queue: Alessio Bazzica <alessiob@webrtc.org>
Reviewed-by: Jakob Ivarsson <jakobi@webrtc.org>
Cr-Commit-Position: refs/heads/master@{#32758}
This commit is contained in:
Alessio Bazzica
2020-11-26 14:32:36 +01:00
committed by Commit Bot
parent 05266ca658
commit e7b5c1a235
1 changed files with 46 additions and 0 deletions
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46
modules/audio_processing/agc2/rnn_vad/rnn_unittest.cc
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@ -30,6 +30,21 @@ namespace rnn_vad {
namespace test {
namespace {
constexpr std::array<float, kFeatureVectorSize> kFeatures = {
-1.00131f, -0.627069f, -7.81097f, 7.86285f, -2.87145f, 3.32365f,
-0.653161f, 0.529839f, -0.425307f, 0.25583f, 0.235094f, 0.230527f,
-0.144687f, 0.182785f, 0.57102f, 0.125039f, 0.479482f, -0.0255439f,
-0.0073141f, -0.147346f, -0.217106f, -0.0846906f, -8.34943f, 3.09065f,
1.42628f, -0.85235f, -0.220207f, -0.811163f, 2.09032f, -2.01425f,
-0.690268f, -0.925327f, -0.541354f, 0.58455f, -0.606726f, -0.0372358f,
0.565991f, 0.435854f, 0.420812f, 0.162198f, -2.13f, 10.0089f};
void WarmUpRnnVad(RnnBasedVad& rnn_vad) {
for (int i = 0; i < 10; ++i) {
rnn_vad.ComputeVadProbability(kFeatures, /*is_silence=*/false);
}
}
void TestFullyConnectedLayer(FullyConnectedLayer* fc,
rtc::ArrayView<const float> input_vector,
rtc::ArrayView<const float> expected_output) {
@ -220,6 +235,37 @@ INSTANTIATE_TEST_SUITE_P(
return info.param.ToString();
});
// Checks that the speech probability is zero with silence.
TEST(RnnVadTest, CheckZeroProbabilityWithSilence) {
RnnBasedVad rnn_vad(GetAvailableCpuFeatures());
WarmUpRnnVad(rnn_vad);
EXPECT_EQ(rnn_vad.ComputeVadProbability(kFeatures, /*is_silence=*/true), 0.f);
}
// Checks that the same output is produced after reset given the same input
// sequence.
TEST(RnnVadTest, CheckRnnVadReset) {
RnnBasedVad rnn_vad(GetAvailableCpuFeatures());
WarmUpRnnVad(rnn_vad);
float pre = rnn_vad.ComputeVadProbability(kFeatures, /*is_silence=*/false);
rnn_vad.Reset();
WarmUpRnnVad(rnn_vad);
float post = rnn_vad.ComputeVadProbability(kFeatures, /*is_silence=*/false);
EXPECT_EQ(pre, post);
}
// Checks that the same output is produced after silence is observed given the
// same input sequence.
TEST(RnnVadTest, CheckRnnVadSilence) {
RnnBasedVad rnn_vad(GetAvailableCpuFeatures());
WarmUpRnnVad(rnn_vad);
float pre = rnn_vad.ComputeVadProbability(kFeatures, /*is_silence=*/false);
rnn_vad.ComputeVadProbability(kFeatures, /*is_silence=*/true);
WarmUpRnnVad(rnn_vad);
float post = rnn_vad.ComputeVadProbability(kFeatures, /*is_silence=*/false);
EXPECT_EQ(pre, post);
}
} // namespace
} // namespace test
} // namespace rnn_vad