Initial commit: FunASR Speech Recognition Toolkit

Add complete FunASR codebase including models, runtime, and documentation.
2026-07-09 22:38:58 +08:00
commit 6116b1f3c6
3683 changed files with 990984 additions and 0 deletions
@@ -0,0 +1,153 @@
+import importlib.util
+import sys
+import types
+from pathlib import Path
+
+import numpy as np
+
+
+REPO_ROOT = Path(__file__).resolve().parents[1]
+SERVICE_PATH = (
+    REPO_ROOT
+    / "examples"
+    / "industrial_data_pretraining"
+    / "fun_asr_nano"
+    / "serve_vllm.py"
+)
+
+
+def load_service_module(monkeypatch):
+    fastapi_stub = types.ModuleType("fastapi")
+
+    class FastAPIStub:
+        def __init__(self, *args, **kwargs):
+            pass
+
+        def on_event(self, *args, **kwargs):
+            return lambda func: func
+
+        def post(self, *args, **kwargs):
+            return lambda func: func
+
+        def websocket(self, *args, **kwargs):
+            return lambda func: func
+
+    fastapi_stub.FastAPI = FastAPIStub
+    fastapi_stub.File = lambda *args, **kwargs: None
+    fastapi_stub.Form = lambda *args, **kwargs: None
+    fastapi_stub.UploadFile = object
+    fastapi_stub.WebSocket = object
+    fastapi_stub.WebSocketDisconnect = Exception
+
+    responses_stub = types.ModuleType("fastapi.responses")
+
+    class JSONResponseStub:
+        def __init__(self, content=None):
+            self.content = content
+
+    responses_stub.JSONResponse = JSONResponseStub
+
+    funasr_stub = types.ModuleType("funasr")
+    funasr_stub.AutoModel = object
+
+    nano_stub = types.ModuleType("funasr.models.fun_asr_nano.inference_vllm")
+    nano_stub.FunASRNanoVLLM = object
+
+    vad_stub = types.ModuleType("funasr.models.fsmn_vad_streaming.dynamic_vad")
+    vad_stub.DynamicStreamingVAD = object
+
+    monkeypatch.setitem(sys.modules, "fastapi", fastapi_stub)
+    monkeypatch.setitem(sys.modules, "fastapi.responses", responses_stub)
+    monkeypatch.setitem(sys.modules, "uvicorn", types.ModuleType("uvicorn"))
+    monkeypatch.setitem(sys.modules, "soundfile", types.ModuleType("soundfile"))
+    monkeypatch.setitem(sys.modules, "torch", types.ModuleType("torch"))
+    monkeypatch.setitem(sys.modules, "funasr", funasr_stub)
+    monkeypatch.setitem(sys.modules, "funasr.models", types.ModuleType("funasr.models"))
+    monkeypatch.setitem(
+        sys.modules,
+        "funasr.models.fun_asr_nano",
+        types.ModuleType("funasr.models.fun_asr_nano"),
+    )
+    monkeypatch.setitem(
+        sys.modules, "funasr.models.fun_asr_nano.inference_vllm", nano_stub
+    )
+    monkeypatch.setitem(
+        sys.modules,
+        "funasr.models.fsmn_vad_streaming",
+        types.ModuleType("funasr.models.fsmn_vad_streaming"),
+    )
+    monkeypatch.setitem(
+        sys.modules, "funasr.models.fsmn_vad_streaming.dynamic_vad", vad_stub
+    )
+
+    module_name = "serve_vllm_under_test"
+    sys.modules.pop(module_name, None)
+    spec = importlib.util.spec_from_file_location(module_name, SERVICE_PATH)
+    module = importlib.util.module_from_spec(spec)
+    assert spec.loader is not None
+    spec.loader.exec_module(module)
+    return module
+
+
+def test_openai_verbose_json_keeps_segment_speaker(monkeypatch):
+    module = load_service_module(monkeypatch)
+
+    response = module.build_openai_verbose_json(
+        {
+            "duration": 1.2,
+            "text": "hello",
+            "segments": [
+                {
+                    "start": 0.0,
+                    "end": 1.2,
+                    "text": "hello",
+                    "words": [{"word": "hello", "start": 0.0, "end": 1.2}],
+                    "speaker": "SPK0",
+                }
+            ],
+        },
+        language="en",
+    )
+
+    assert response["segments"][0]["speaker"] == "SPK0"
+
+
+def test_process_audio_downmixes_stereo_before_resampling(monkeypatch):
+    module = load_service_module(monkeypatch)
+    captured = {}
+
+    librosa_stub = types.ModuleType("librosa")
+
+    def fake_resample(audio, orig_sr, target_sr):
+        assert audio.ndim == 1
+        captured["resample_input"] = audio.copy()
+        assert orig_sr == 8000
+        assert target_sr == 16000
+        return np.repeat(audio, 2)
+
+    librosa_stub.resample = fake_resample
+    monkeypatch.setitem(sys.modules, "librosa", librosa_stub)
+
+    class EngineStub:
+        def generate(self, inputs, **kwargs):
+            captured["engine_input"] = inputs[0]
+            return [{"text": "ok"}]
+
+    module._engine = EngineStub()
+    stereo_audio = np.column_stack(
+        [np.zeros(8000, dtype=np.float32), np.ones(8000, dtype=np.float32)]
+    )
+
+    result = module.process_audio(
+        stereo_audio,
+        sr=8000,
+        use_vad=False,
+        use_spk=False,
+        use_timestamp=False,
+    )
+
+    assert np.allclose(captured["resample_input"], 0.5)
+    assert captured["engine_input"].shape == (16000,)
+    assert np.allclose(captured["engine_input"], 0.5)
+    assert result["duration"] == 1.0
+    assert result["text"] == "ok"