Add C++ runtime for speaker verification models from NeMo (#527)

sherpa-onnx/python/tests/test_speaker_recognition.py

@@ -56,7 +56,7 @@ def load_speaker_embedding_model(model_filename):
     return extractor
 
 
-def test_wespeaker_model(model_filename: str):
+def test_zh_models(model_filename: str):
     model_filename = str(model_filename)
     if "en" in model_filename:
         print(f"skip {model_filename}")
@@ -114,8 +114,9 @@ def test_wespeaker_model(model_filename: str):
         assert ans == name, (name, ans)
 
 
-def test_3dspeaker_model(model_filename: str):
-    extractor = load_speaker_embedding_model(str(model_filename))
+def test_en_and_zh_models(model_filename: str):
+    model_filename = str(model_filename)
+    extractor = load_speaker_embedding_model(model_filename)
     manager = sherpa_onnx.SpeakerEmbeddingManager(extractor.dim)
 
     filenames = [
@@ -124,7 +125,14 @@ def test_3dspeaker_model(model_filename: str):
         "speaker1_a_en_16k",
         "speaker2_a_en_16k",
     ]
+    is_en = "en" in model_filename
     for filename in filenames:
+        if is_en and "cn" in filename:
+            continue
+
+        if not is_en and "en" in filename:
+            continue
+
         name = filename.rsplit("_", maxsplit=1)[0]
         data, sample_rate = read_wave(
             f"/tmp/sr-models/sr-data/test/3d-speaker/{filename}.wav"
@@ -145,6 +153,11 @@ def test_3dspeaker_model(model_filename: str):
         "speaker1_b_en_16k",
     ]
     for filename in filenames:
+        if is_en and "cn" in filename:
+            continue
+
+        if not is_en and "en" in filename:
+            continue
         print(filename)
         name = filename.rsplit("_", maxsplit=1)[0]
         name = name.replace("b_cn", "a_cn")
@@ -178,7 +191,8 @@ class TestSpeakerRecognition(unittest.TestCase):
             return
         for filename in model_dir.glob("*.onnx"):
             print(filename)
-            test_wespeaker_model(filename)
+            test_zh_models(filename)
+            test_en_and_zh_models(filename)
 
     def test_3dpeaker_models(self):
         model_dir = Path(d) / "3dspeaker"
@@ -187,7 +201,16 @@ class TestSpeakerRecognition(unittest.TestCase):
             return
         for filename in model_dir.glob("*.onnx"):
             print(filename)
-            test_3dspeaker_model(filename)
+            test_en_and_zh_models(filename)
+
+    def test_nemo_models(self):
+        model_dir = Path(d) / "nemo"
+        if not model_dir.is_dir():
+            print(f"{model_dir} does not exist - skip it")
+            return
+        for filename in model_dir.glob("*.onnx"):
+            print(filename)
+            test_en_and_zh_models(filename)
 
 
 if __name__ == "__main__":