APM Quality Assessment tool, environmental noise generator

webrtc/modules/audio_processing/test/py_quality_assessment/quality_assessment/signal_processing_unittest.py

Index: webrtc/modules/audio_processing/test/py_quality_assessment/quality_assessment/signal_processing_unittest.py
diff --git a/webrtc/modules/audio_processing/test/py_quality_assessment/quality_assessment/signal_processing_unittest.py b/webrtc/modules/audio_processing/test/py_quality_assessment/quality_assessment/signal_processing_unittest.py
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index 0000000000000000000000000000000000000000..82b138c4a443b3e8806321117b4fe8d894f4f319
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+++ b/webrtc/modules/audio_processing/test/py_quality_assessment/quality_assessment/signal_processing_unittest.py
@@ -0,0 +1,70 @@
+# Copyright (c) 2017 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.
+
+import unittest
+
+import numpy as np
+import pydub
+
+from . import signal_processing
+
+class TestSignalProcessing(unittest.TestCase):
+
+  def testMixSignals(self):
+    # Generate a template signal with which white noise can be generated.
+    silence = pydub.AudioSegment.silent(duration=1000, frame_rate=48000)
+
+    # Generate two distinct AudioSegment instances with 1 second of white noise.
+    signal = signal_processing.SignalProcessingUtils.generate_white_noise(
+        silence)
+    noise = signal_processing.SignalProcessingUtils.generate_white_noise(
+        silence)
+
+    # Extract samples.
+    signal_samples = signal.get_array_of_samples()
+    noise_samples = noise.get_array_of_samples()
+
+    # Test target SNR -Inf (noise expected).
+    mix_neg_inf = signal_processing.SignalProcessingUtils.mix_signals(
+        signal, noise, -np.Inf)
+    self.assertTrue(len(noise), len(mix_neg_inf))  # Check duration.
+    mix_neg_inf_samples = mix_neg_inf.get_array_of_samples()
+    self.assertTrue(  # Check samples.
+        all([x == y for x, y in zip(noise_samples, mix_neg_inf_samples)]))
+
+    # Test target SNR 0.0 (different data expected).
+    mix_0 = signal_processing.SignalProcessingUtils.mix_signals(
+        signal, noise, 0.0)
+    self.assertTrue(len(signal), len(mix_0))  # Check duration.
+    self.assertTrue(len(noise), len(mix_0))
+    mix_0_samples = mix_0.get_array_of_samples()
+    self.assertTrue(
+        any([x != y for x, y in zip(signal_samples, mix_0_samples)]))
+    self.assertTrue(
+        any([x != y for x, y in zip(noise_samples, mix_0_samples)]))
+
+    # Test target SNR +Inf (signal expected).
+    mix_pos_inf = signal_processing.SignalProcessingUtils.mix_signals(
+        signal, noise, np.Inf)
+    self.assertTrue(len(signal), len(mix_pos_inf))  # Check duration.
+    mix_pos_inf_samples = mix_pos_inf.get_array_of_samples()
+    self.assertTrue(  # Check samples.
+        all([x == y for x, y in zip(signal_samples, mix_pos_inf_samples)]))
+
+  def testMixSignalsMinInfPower(self):
+    silence = pydub.AudioSegment.silent(duration=1000, frame_rate=48000)
+    signal = signal_processing.SignalProcessingUtils.generate_white_noise(
+        silence)
+
+    with self.assertRaises(signal_processing.SignalProcessingException):
+      _ = signal_processing.SignalProcessingUtils.mix_signals(
+          signal, silence, 0.0)
+
+    with self.assertRaises(signal_processing.SignalProcessingException):
+      _ = signal_processing.SignalProcessingUtils.mix_signals(
+          silence, signal, 0.0)