update unittest

tests/test_sv_inference_pipeline.py

@@ -0,0 +1,47 @@
+import unittest
+
+from modelscope.pipelines import pipeline
+from modelscope.utils.constant import Tasks
+from modelscope.utils.logger import get_logger
+
+logger = get_logger()
+
+
+class TestXVectorInferencePipelines(unittest.TestCase):
+    def test_funasr_path(self):
+        import funasr
+        import os
+        logger.info("run_dir:{0} ; funasr_path: {1}".format(os.getcwd(), funasr.__file__))
+
+    def test_inference_pipeline(self):
+        inference_sv_pipline = pipeline(
+            task=Tasks.speaker_verification,
+            model='damo/speech_xvector_sv-zh-cn-cnceleb-16k-spk3465-pytorch'
+        )
+        # 提取不同句子的说话人嵌入码
+        rec_result = inference_sv_pipline(
+            audio_in='https://isv-data.oss-cn-hangzhou.aliyuncs.com/ics/MaaS/ASR/test_audio/sv_example_enroll.wav')
+        enroll = rec_result["spk_embedding"]
+
+        rec_result = inference_sv_pipline(
+            audio_in='https://isv-data.oss-cn-hangzhou.aliyuncs.com/ics/MaaS/ASR/test_audio/sv_example_same.wav')
+        same = rec_result["spk_embedding"]
+
+        rec_result = inference_sv_pipline(
+            audio_in='https://isv-data.oss-cn-hangzhou.aliyuncs.com/ics/MaaS/ASR/test_audio/sv_example_different.wav')
+        different = rec_result["spk_embedding"]
+
+        # 对相同的说话人计算余弦相似度
+        sv_threshold = 0.9465
+        same_cos = np.sum(enroll * same) / (np.linalg.norm(enroll) * np.linalg.norm(same))
+        same_cos = max(same_cos - sv_threshold, 0.0) / (1.0 - sv_threshold) * 100.0
+        logger.info("Similarity: {}".format(same_cos))
+
+        # 对不同的说话人计算余弦相似度
+        diff_cos = np.sum(enroll * different) / (np.linalg.norm(enroll) * np.linalg.norm(different))
+        diff_cos = max(diff_cos - sv_threshold, 0.0) / (1.0 - sv_threshold) * 100.0
+        logger.info("Similarity: {}".format(diff_cos))
+
+
+if __name__ == '__main__':
+    unittest.main()