[本地语音降噪]：完成本地语音链路和噪音过滤，包含降噪模型、本地ASR和实时字幕稳定策略

tests/test_audio_preprocess.py

@@ -0,0 +1,97 @@
+from __future__ import annotations
+
+import tempfile
+import unittest
+from pathlib import Path
+
+from owner_voice_pet.audio_preprocess import SherpaOnnxDenoiserPreprocessor
+from owner_voice_pet.models import AudioFrame, ErrorCode, ProviderError
+from owner_voice_pet.speech_models import DEFAULT_DENOISER_PATH
+
+
+class FakeDenoisedAudio:
+    def __init__(self, samples, sample_rate: int) -> None:
+        self.samples = samples
+        self.sample_rate = sample_rate
+
+
+class FakeSherpa:
+    class OfflineSpeechDenoiserGtcrnModelConfig:
+        def __init__(self, model: str) -> None:
+            self.model = model
+
+    class OfflineSpeechDenoiserModelConfig:
+        def __init__(self, gtcrn, num_threads: int, provider: str) -> None:
+            self.gtcrn = gtcrn
+            self.num_threads = num_threads
+            self.provider = provider
+
+    class OnlineSpeechDenoiserConfig:
+        def __init__(self, model) -> None:
+            self.model = model
+
+    class OnlineSpeechDenoiser:
+        def __init__(self, config) -> None:
+            self.config = config
+            self.reset_called = False
+
+        def run(self, samples, sample_rate: int):
+            import numpy as np
+
+            return FakeDenoisedAudio(np.zeros_like(samples, dtype=np.float32), sample_rate)
+
+        def reset(self) -> None:
+            self.reset_called = True
+
+
+class FailingSherpa(FakeSherpa):
+    class OnlineSpeechDenoiser(FakeSherpa.OnlineSpeechDenoiser):
+        def run(self, samples, sample_rate: int):
+            raise RuntimeError("denoise failed")
+
+
+class AudioPreprocessTests(unittest.TestCase):
+    def test_denoiser_missing_model_is_structured(self) -> None:
+        with tempfile.TemporaryDirectory() as tmp:
+            provider = SherpaOnnxDenoiserPreprocessor(tmp, sherpa_module=FakeSherpa)
+            with self.assertRaises(ProviderError) as raised:
+                provider.load()
+        self.assertEqual(raised.exception.code, ErrorCode.NOISE_FILTER_MODEL_MISSING)
+
+    def test_denoiser_processes_frame_and_marks_metadata(self) -> None:
+        with tempfile.TemporaryDirectory() as tmp:
+            model = Path(tmp) / DEFAULT_DENOISER_PATH
+            model.parent.mkdir(parents=True)
+            model.write_bytes(b"fake")
+            provider = SherpaOnnxDenoiserPreprocessor(tmp, sherpa_module=FakeSherpa)
+            provider.load()
+            frame = AudioFrame(
+                b"\xff\x7f",
+                16000,
+                1,
+                100,
+                7,
+                {"duration_ms": 20, "speech": True},
+            )
+            processed = provider.process_frame(frame)
+
+        self.assertNotEqual(processed.pcm, frame.pcm)
+        self.assertTrue(processed.metadata["denoised"])
+        self.assertEqual(processed.metadata["noise_filter_provider"], "sherpa_onnx_gtcrn")
+        self.assertEqual(processed.timestamp_ms, 100)
+        self.assertEqual(processed.frame_id, 7)
+
+    def test_denoiser_runtime_failure_is_structured(self) -> None:
+        with tempfile.TemporaryDirectory() as tmp:
+            model = Path(tmp) / DEFAULT_DENOISER_PATH
+            model.parent.mkdir(parents=True)
+            model.write_bytes(b"fake")
+            provider = SherpaOnnxDenoiserPreprocessor(tmp, sherpa_module=FailingSherpa)
+            provider.load()
+            with self.assertRaises(ProviderError) as raised:
+                provider.process_frame(AudioFrame(b"\xff\x7f", 16000, 1, 0, 0))
+        self.assertEqual(raised.exception.code, ErrorCode.NOISE_FILTER_FAILED)
+
+
+if __name__ == "__main__":
+    unittest.main()