Merge branch 'main' of https://github.com/alibaba-damo-academy/FunASR into ...

雾聪

2023-06-16 2e6011f44848ad48e131086645fd5d9a9b77f5b5

Merge branch 'main' of https://github.com/alibaba-damo-academy/FunASR into main

 egs_modelscope/speaker_diarization/speech_diarization_sond-zh-cn-alimeeting-16k-n16k4-pytorch/infer.py

@@ -17,7 +17,7 @@
    diar_model_config="sond.yaml",
    model='damo/speech_diarization_sond-zh-cn-alimeeting-16k-n16k4-pytorch',
    sv_model="damo/speech_xvector_sv-zh-cn-cnceleb-16k-spk3465-pytorch",
    sv_model_revision="master",
    sv_model_revision="v1.2.2",
)

# use audio_list as the input, where the first one is the record to be detected

 funasr/runtime/websocket/readme.md

@@ -51,7 +51,7 @@


```shell

cd bin

   ./funasr-wss-server  [--model_thread_num <int>] [--decoder_thread_num <int>]

./funasr-wss-server  [--model_thread_num <int>] [--decoder_thread_num <int>]

                    [--io_thread_num <int>] [--port <int>] [--listen_ip

                    <string>] [--punc-quant <string>] [--punc-dir <string>]

                    [--vad-quant <string>] [--vad-dir <string>] [--quantize

@@ -85,7 +85,7 @@
     default: ../../../ssl_key/server.key, path of keyfile for WSS connection

  

example:

   funasr-wss-server --model-dir /FunASR/funasr/runtime/onnxruntime/export/damo/speech_paraformer-large_asr_nat-zh-cn-16k-common-vocab8404-pytorch

./funasr-wss-server --model-dir /FunASR/funasr/runtime/onnxruntime/export/damo/speech_paraformer-large_asr_nat-zh-cn-16k-common-vocab8404-pytorch

```



## Run websocket client test


 tests/test_sv_inference_pipeline.py

@@ -19,30 +19,20 @@
            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))

        # the same speaker
        rec_result = inference_sv_pipline(audio_in=(
            'https://isv-data.oss-cn-hangzhou.aliyuncs.com/ics/MaaS/ASR/test_audio/sv_example_enroll.wav',
            'https://isv-data.oss-cn-hangzhou.aliyuncs.com/ics/MaaS/ASR/test_audio/sv_example_same.wav'))
        assert abs(rec_result["scores"][0]-0.85) < 0.1 and abs(rec_result["scores"][1]-0.14) < 0.1
        logger.info(f"Similarity {rec_result['scores']}")
    
        # different speaker
        rec_result = inference_sv_pipline(audio_in=(
            'https://isv-data.oss-cn-hangzhou.aliyuncs.com/ics/MaaS/ASR/test_audio/sv_example_enroll.wav',
            'https://isv-data.oss-cn-hangzhou.aliyuncs.com/ics/MaaS/ASR/test_audio/sv_example_different.wav'))
        assert abs(rec_result["scores"][0]-0.0) < 0.1 and abs(rec_result["scores"][1]-1.0) < 0.1
        logger.info(f"Similarity {rec_result['scores']}")

if __name__ == '__main__':
    unittest.main()