public float[][] CreateSpectrogram(AudioSamples audioSamples, int overlap, int wdftSize) { float[] window = new DefaultSpectrogramConfig().Window.GetWindow(wdftSize); float[] samples = audioSamples.Samples; int width = (samples.Length - wdftSize) / overlap; float[][] frames = new float[width][]; for (int i = 0; i < width; i++) { float[] complexSignal = fftService.FFTForward(samples, i * overlap, wdftSize, window); float[] band = new float[(wdftSize / 2) + 1]; for (int j = 0; j < (wdftSize / 2) + 1; j++) { double re = complexSignal[2 * j]; double img = complexSignal[(2 * j) + 1]; re /= (float)wdftSize / 2; img /= (float)wdftSize / 2; band[j] = (float)((re * re) + (img * img)); } frames[i] = band; } return frames; }
public LomontFFT() { A = 0; B = 1; var config = new DefaultSpectrogramConfig(); Initialize(config.WdftSize); }
public DefaultFingerprintConfiguration() { SpectrogramConfig = new DefaultSpectrogramConfig(); HashingConfig = new DefaultHashingConfig(); TopWavelets = 200; SampleRate = 5512; NormalizeSignal = false; Clusters = Enumerable.Empty<string>(); }
public void CreateLogSpectrogramFromSamplesLessThanFourierTransformWindowLength() { var configuration = new DefaultSpectrogramConfig(); var samples = TestUtilities.GenerateRandomAudioSamples(configuration.WdftSize - 1); var result = spectrumService.CreateLogSpectrogram(samples, configuration); Assert.AreEqual(0, result.Count); }
public DefaultFingerprintConfiguration() { SpectrogramConfig = new DefaultSpectrogramConfig(); HashingConfig = new DefaultHashingConfig(); TopWavelets = 200; SampleRate = 5512; NormalizeSignal = false; Clusters = Enumerable.Empty <string>(); }
public DefaultFingerprintConfiguration() { SpectrogramConfig = new DefaultSpectrogramConfig(); HashingConfig = new DefaultHashingConfig(); TopWavelets = 200; SampleRate = 5512; HaarWaveletNorm = System.Math.Sqrt(2); Clusters = Enumerable.Empty <string>(); }
public DefaultFingerprintConfiguration() { SpectrogramConfig = new DefaultSpectrogramConfig(); HashingConfig = new DefaultHashingConfig(); TopWavelets = 200; SampleRate = 5512; HaarWaveletNorm = System.Math.Sqrt(2); FingerprintLengthInSeconds = (double)SamplesPerFingerprint / SampleRate; OriginalPointSaveTransform = null; }
public void CutLogarithmizedSpectrumOfJustOneFingerprintTest() { var stride = new StaticStride(0, 0); var configuration = new DefaultSpectrogramConfig { Stride = stride }; int logSpectrumLength = configuration.ImageLength; // 128 var logSpectrum = GetLogSpectrum(logSpectrumLength); var cutLogarithmizedSpectrum = spectrumService.CutLogarithmizedSpectrum(logSpectrum, SampleRate, configuration); Assert.AreEqual(1, cutLogarithmizedSpectrum.Count); }
public void CreateLogSpectrogramFromMinimalSamplesLengthTest() { var configuration = new DefaultSpectrogramConfig { NormalizeSignal = false }; var samples = TestUtilities.GenerateRandomAudioSamples(new DefaultFingerprintConfiguration().SamplesPerFingerprint + configuration.WdftSize); // 8192 + 2048 SetupFftService(configuration, samples); var result = spectrumService.CreateLogSpectrogram(samples, configuration); logUtility.Verify(utility => utility.GenerateLogFrequenciesRanges(SampleRate, configuration), Times.Once()); Assert.AreEqual(1, result.Count); Assert.AreEqual(configuration.ImageLength, result[0].Image.Length); }
public DefaultFingerprintConfiguration() { SpectrogramConfig = new DefaultSpectrogramConfig(); HashingConfig = new DefaultHashingConfig(); TopWavelets = 200; SampleRate = 5512; HaarWaveletNorm = Math.Sqrt(2); FingerprintLengthInSeconds = (double)SamplesPerFingerprint / SampleRate; OriginalPointSaveTransform = (_ => Array.Empty <byte>()); GaussianBlurConfiguration = GaussianBlurConfiguration.None; FrameNormalizationTransform = new LogSpectrumNormalization(); }
public void CreateLogSpectrogramTest() { var configuration = new DefaultSpectrogramConfig { ImageLength = 2048 }; var samples = TestUtilities.GenerateRandomAudioSamples((configuration.Overlap * configuration.WdftSize) + configuration.WdftSize); // 64 * 2048 SetupFftService(configuration, samples); var result = spectrumService.CreateLogSpectrogram(samples, configuration); logUtility.Verify(utility => utility.GenerateLogFrequenciesRanges(SampleRate, configuration), Times.Once()); Assert.AreEqual(1, result.Count); Assert.AreEqual(configuration.WdftSize, result[0].Image.Length); Assert.AreEqual(32, result[0].Image[0].Length); }
public void CutLogarithmizedSpectrumTest() { var stride = new StaticStride(0, 0); var configuration = new DefaultSpectrogramConfig { Stride = stride }; const int LogSpectrumLength = 1024; var logSpectrum = GetLogSpectrum(LogSpectrumLength); var cutLogarithmizedSpectrum = spectrumService.CutLogarithmizedSpectrum(logSpectrum, SampleRate, configuration); Assert.AreEqual(8, cutLogarithmizedSpectrum.Count); double lengthOfOneFingerprint = (double)configuration.ImageLength * configuration.Overlap / SampleRate; for (int i = 0; i < cutLogarithmizedSpectrum.Count; i++) { Assert.IsTrue( System.Math.Abs(cutLogarithmizedSpectrum[i].StartsAt - (i * lengthOfOneFingerprint)) < Epsilon); } }
public void GenerateLogFrequenciesRangesTest() { var defaultConfig = new DefaultSpectrogramConfig { UseDynamicLogBase = false, LogBase = 10 }; float[] logSpacedFrequencies = new[] // generated in matlab with logspace(2.50242712, 3.3010299957, 33) { 318.00f, 336.81f, 356.73f, 377.83f, 400.18f, 423.85f, 448.92f, 475.47f, 503.59f, 533.38f, 564.92f, 598.34f, 633.73f, 671.21f, 710.91f, 752.96f, 797.50f, 844.67f, 894.63f, 947.54f, 1003.58f, 1062.94f, 1125.81f, 1192.40f, 1262.93f, 1337.63f, 1416.75f, 1500.54f, 1589.30f, 1683.30f, 1782.86f, 1888.31f, 2000f }; int[] indexes = logUtility.GenerateLogFrequenciesRanges(defaultFingerprintConfiguration.SampleRate, defaultConfig); for (int i = 0; i < logSpacedFrequencies.Length; i++) { var logSpacedFrequency = logSpacedFrequencies[i]; int index = logUtility.FrequencyToSpectrumIndex(logSpacedFrequency, defaultFingerprintConfiguration.SampleRate, defaultConfig.WdftSize); Assert.AreEqual(index, indexes[i]); } }
public void CutLogarithmizedSpectrumWithSpectrumWhichIsLessThanMinimalLengthOfOneFingerprintTest() { var stride = new StaticStride(0, 0); var config = new DefaultSpectrogramConfig { Stride = stride }; int logSpectrumLength = config.ImageLength - 1; var logSpectrum = GetLogSpectrum(logSpectrumLength); var cutLogarithmizedSpectrum = spectrumService.CutLogarithmizedSpectrum(logSpectrum, SampleRate, config); Assert.AreEqual(0, cutLogarithmizedSpectrum.Count); }
public void ShouldCreateCorrectNumberOfSubFingerprints() { var configuration = new DefaultSpectrogramConfig { Stride = new StaticStride(0) }; var tenMinutes = 10 * 60; var samples = TestUtilities.GenerateRandomAudioSamples(tenMinutes * SampleRate); SetupFftService(configuration, samples); var result = spectrumService.CreateLogSpectrogram(samples, configuration); Assert.AreEqual((tenMinutes * SampleRate) / (configuration.ImageLength * configuration.Overlap), result.Count); }
private void SetupFftService(DefaultSpectrogramConfig configuration, AudioSamples samples) { logUtility.Setup(utility => utility.GenerateLogFrequenciesRanges(SampleRate, configuration)) .Returns(new[] { 118, 125, 133, 141, 149, 158, 167, 177, 187, 198, 210, 223, 236, 250, 264, 280, 297, 314, 333, 352, 373, 395, 419, 443, 470, 497, 527, 558, 591, 626, 663, 702, 744, }); fftService.Setup(service => service.FFTForward(samples.Samples, It.IsAny<int>(), configuration.WdftSize, It.IsAny<float[]>())) .Returns(TestUtilities.GenerateRandomFloatArray(2048)); }
public void CutLogarithmizedSpectrumWithDefaultStride() { var config = new DefaultSpectrogramConfig(); int logSpectrumlength = config.ImageLength * 10; var logSpectrum = GetLogSpectrum(logSpectrumlength); var cutLogarithmizedSpectrum = spectrumService.CutLogarithmizedSpectrum(logSpectrum, SampleRate, config); // Default stride between 2 consecutive images is 1536, but because of rounding issues and the fact // that minimal step is 11.6 ms, timestamp is roughly .37155 sec const double TimestampOfFingerprints = (double)1536 / SampleRate; Assert.AreEqual(49, cutLogarithmizedSpectrum.Count); for (int i = 0; i < cutLogarithmizedSpectrum.Count; i++) { Assert.IsTrue(System.Math.Abs(cutLogarithmizedSpectrum[i].StartsAt - (i * TimestampOfFingerprints)) < Epsilon); } }
public void CutLogarithmizedSpectrumWithAnIncrementalStaticStride() { var stride = new IncrementalStaticStride(new DefaultFingerprintConfiguration().SamplesPerFingerprint / 2); var config = new DefaultSpectrogramConfig { Stride = stride }; int logSpectrumLength = (config.ImageLength * 24) + config.Overlap; var logSpectrum = GetLogSpectrum(logSpectrumLength); var cutLogarithmizedSpectrum = spectrumService.CutLogarithmizedSpectrum(logSpectrum, SampleRate, config); Assert.AreEqual(48, cutLogarithmizedSpectrum.Count); double lengthOfOneFingerprint = (double)config.ImageLength * config.Overlap / SampleRate; for (int i = 0; i < cutLogarithmizedSpectrum.Count; i++) { Assert.IsTrue(System.Math.Abs(cutLogarithmizedSpectrum[i].StartsAt - (i * lengthOfOneFingerprint / 2)) < Epsilon); } }