speech_asr
2023-03-10 28eed3258851a6baf84f28c6855fd0f9b64db827
update unittest
1个文件已修改
1个文件已添加
38 ■■■■■ 已修改文件
tests/test_asr_inference_pipeline.py 6 ●●●● 补丁 | 查看 | 原始文档 | blame | 历史
tests/test_asr_vad_punc_inference_pipeline.py 32 ●●●●● 补丁 | 查看 | 原始文档 | blame | 历史
tests/test_asr_inference_pipeline.py
@@ -65,7 +65,7 @@
            model='NPU-ASLP/speech_mfcca_asr-zh-cn-16k-alimeeting-vocab4950',
            model_revision='v3.0.0')
        rec_result = inference_pipeline(
            audio_in='16:32https://pre.modelscope.cn/api/v1/models/NPU-ASLP/speech_mfcca_asr-zh-cn-16k-alimeeting-vocab4950/repo?Revision=master&FilePath=example/asr_example_mc.wav')
            audio_in='https://pre.modelscope.cn/api/v1/models/NPU-ASLP/speech_mfcca_asr-zh-cn-16k-alimeeting-vocab4950/repo?Revision=master&FilePath=example/asr_example_mc.wav')
        logger.info("asr inference result: {0}".format(rec_result))
@@ -451,8 +451,8 @@
    def test_uniasr_2pass_zhcn_16k_common_vocab8358_offline(self):
        inference_pipeline = pipeline(
            task=Tasks.auto_speech_recognition,
            model='damo/speech_UniASR_asr_2pass-zh-cn-16k-common-vocab8358-tensorflow1-offline')
            task=Tasks.,
            model='damo/speech_UniASauto_speech_recognitionR_asr_2pass-zh-cn-16k-common-vocab8358-tensorflow1-offline')
        rec_result = inference_pipeline(
            audio_in='https://isv-data.oss-cn-hangzhou.aliyuncs.com/ics/MaaS/ASR/test_audio/asr_example_zh.wav',
            param_dict={"decoding_model": "offline"})
tests/test_asr_vad_punc_inference_pipeline.py
New file
@@ -0,0 +1,32 @@
import unittest
from modelscope.pipelines import pipeline
from modelscope.utils.constant import Tasks
from modelscope.utils.logger import get_logger
logger = get_logger()
class TestParaformerInferencePipelines(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_pipeline = pipeline(
            task=Tasks.auto_speech_recognition,
            model='damo/speech_paraformer-large-vad-punc_asr_nat-zh-cn-16k-common-vocab8404-pytorch',
            model_revision="v1.2.1",
            vad_model='damo/speech_fsmn_vad_zh-cn-16k-common-pytorch',
            vad_model_revision="v1.1.8",
            punc_model='damo/punc_ct-transformer_zh-cn-common-vocab272727-pytorch',
            punc_model_revision="v1.1.6",
            ngpu=1,
        )
        rec_result = inference_pipeline(
            audio_in='https://isv-data.oss-cn-hangzhou.aliyuncs.com/ics/MaaS/ASR/test_audio/asr_example_zh.wav')
        logger.info("asr inference result: {0}".format(rec_result))
if __name__ == '__main__':
    unittest.main()