[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_live_runtime.py

@@ -24,7 +24,7 @@ from owner_voice_pet.llm import MockLlmProvider
 from owner_voice_pet.models import AudioFrame, AudioSegment, Transcript
 from owner_voice_pet.assistant_pipeline import VoiceAssistantPipeline
 from owner_voice_pet.runtime import build_live_runtime
-from owner_voice_pet.stt import MetadataSttProvider
+from owner_voice_pet.stt import MetadataSttProvider, SherpaOnnxSttProvider
 from owner_voice_pet.transport import MemoryAudioTransport
 from owner_voice_pet.tts import SineTtsProvider
 from owner_voice_pet.vad import EnergyVadProvider, PrimarySpeakerVadRecorder, VadRecorder
@@ -97,10 +97,43 @@ class RecordingReporter:
         self.errors.append(f"{stage}:{code}:{message}")
 
 
+class MarkerAudioPreprocessor:
+    def __init__(self, partial_text: str = "降噪后问题") -> None:
+        self.partial_text = partial_text
+        self.loaded = False
+        self.reset_calls = 0
+        self.frames: list[AudioFrame] = []
+
+    def load(self) -> None:
+        self.loaded = True
+
+    def reset(self) -> None:
+        self.reset_calls += 1
+
+    def process_frame(self, frame: AudioFrame) -> AudioFrame:
+        metadata = dict(frame.metadata)
+        metadata["denoised"] = True
+        metadata["partial_transcript"] = self.partial_text
+        processed = AudioFrame(
+            b"\x01\x00",
+            frame.sample_rate,
+            frame.channels,
+            frame.timestamp_ms,
+            frame.frame_id,
+            metadata,
+        )
+        self.frames.append(processed)
+        return processed
+
+    def flush(self) -> list[AudioFrame]:
+        return []
+
+
 def make_runtime(
     texts: list[str],
     context: ConversationContext | None = None,
     partial_texts: list[list[str]] | None = None,
+    audio_preprocessor: MarkerAudioPreprocessor | None = None,
 ) -> tuple[VoiceAssistantPipeline, QueueSttProvider, MockLlmProvider, MemoryAudioTransport, RecordingReporter]:
     frames = []
     for idx, _text in enumerate(texts):
@@ -121,6 +154,7 @@ def make_runtime(
         wakeword=KeywordWakeWordProvider(),
         vad_recorder=VadRecorder(EnergyVadProvider(), min_duration_ms=40, end_silence_ms=40),
         stt=stt,
+        audio_preprocessor=audio_preprocessor,
         realtime_stt=MetadataSttProvider() if partial_texts is not None else None,
         llm=llm,
         tts=tts,
@@ -200,7 +234,7 @@ class LiveRuntimeTests(unittest.TestCase):
         runtime, _, llm, _, reporter = make_runtime(["第一问"], partial_texts=[["第一", "第一问"]])
         runtime.run(max_turns=1)
 
-        self.assertEqual(reporter.partials, ["第一", "第一问"])
+        self.assertEqual(reporter.partials, ["第一问"])
         self.assertEqual(reporter.transcripts, ["第一问"])
         self.assertEqual(llm.calls[0][-1].content, "第一问")
         event_types = [event.type for event in runtime.event_bus.events]
@@ -208,6 +242,22 @@ class LiveRuntimeTests(unittest.TestCase):
         self.assertLess(event_types.index(TRANSCRIPT_PARTIAL), event_types.index(SPEECH_ENDED))
         self.assertLess(event_types.index(TRANSCRIPT_PARTIAL), event_types.index(TRANSCRIPT_FINAL))
 
+    def test_capture_uses_denoised_frames_for_partial_and_final_stt(self) -> None:
+        preprocessor = MarkerAudioPreprocessor(partial_text="降噪后问题")
+        runtime, stt, _, _, reporter = make_runtime(
+            ["第一问"],
+            partial_texts=[["原始噪声", "原始噪声"]],
+            audio_preprocessor=preprocessor,
+        )
+        runtime.run(max_turns=1)
+
+        self.assertTrue(preprocessor.loaded)
+        self.assertGreaterEqual(preprocessor.reset_calls, 1)
+        self.assertEqual(reporter.partials, ["降噪后问题"])
+        self.assertEqual(len(stt.calls), 1)
+        self.assertTrue(stt.calls[0].metadata["denoised"])
+        self.assertIn(b"\x01\x00", stt.calls[0].pcm)
+
     def test_wake_keyword_does_not_pollute_llm_user_message(self) -> None:
         runtime, _, llm, _, _ = make_runtime(["第一问"])
         runtime.run(max_turns=1)
@@ -218,6 +268,8 @@ class LiveRuntimeTests(unittest.TestCase):
     def test_live_runtime_uses_primary_speaker_endpoint_by_default(self) -> None:
         runtime = build_live_runtime(AppConfig(llm_api_key="secret"))
         self.assertIsInstance(runtime.vad_recorder, PrimarySpeakerVadRecorder)
+        self.assertEqual(runtime.config.speech_provider, "local")
+        self.assertIsInstance(runtime.stt, SherpaOnnxSttProvider)
         self.assertIsNotNone(runtime.realtime_stt)