From 28ccfbfc51068a663a80764e14074df5edf2b5ba Mon Sep 17 00:00:00 2001 From: kongdeqiang <kongdeqiang960204@163.com> Date: 星期五, 13 三月 2026 17:41:41 +0800 Subject: [PATCH] 提交 --- examples/industrial_data_pretraining/seaco_paraformer/demo.py | 46 ++++++++++++++++++++++++++++++++++++---------- 1 files changed, 36 insertions(+), 10 deletions(-) diff --git a/examples/industrial_data_pretraining/seaco_paraformer/demo.py b/examples/industrial_data_pretraining/seaco_paraformer/demo.py index 7f1fdb5..a88e880 100644 --- a/examples/industrial_data_pretraining/seaco_paraformer/demo.py +++ b/examples/industrial_data_pretraining/seaco_paraformer/demo.py @@ -5,14 +5,40 @@ from funasr import AutoModel -model = AutoModel(model="damo/speech_seaco_paraformer_large_asr_nat-zh-cn-16k-common-vocab8404-pytorch", - model_revision="v2.0.0", - vad_model="damo/speech_fsmn_vad_zh-cn-16k-common-pytorch", - vad_model_revision="v2.0.2", - punc_model="damo/punc_ct-transformer_zh-cn-common-vocab272727-pytorch", - punc_model_revision="v2.0.1", - ) +model = AutoModel( + model="iic/speech_seaco_paraformer_large_asr_nat-zh-cn-16k-common-vocab8404-pytorch", + # vad_model="iic/speech_fsmn_vad_zh-cn-16k-common-pytorch", + # punc_model="iic/punc_ct-transformer_zh-cn-common-vocab272727-pytorch", + # spk_model="iic/speech_campplus_sv_zh-cn_16k-common", +) -res = model(input="https://isv-data.oss-cn-hangzhou.aliyuncs.com/ics/MaaS/ASR/test_audio/asr_example_zh.wav", - hotword='杈炬懇闄� 纾ㄦ惌') -print(res) \ No newline at end of file + +# example1 +res = model.generate( + input="https://isv-data.oss-cn-hangzhou.aliyuncs.com/ics/MaaS/ASR/test_audio/asr_example_zh.wav", + hotword="杈炬懇闄� 榄旀惌", + # return_raw_text=True, # return raw text recognition results splited by space of equal length with timestamp + # preset_spk_num=2, # preset speaker num for speaker cluster model + # sentence_timestamp=True, # return sentence level information when spk_model is not given +) +print(res) + + +""" +# tensor or numpy as input +# example2 +import torchaudio +import os +wav_file = os.path.join(model.model_path, "example/asr_example.wav") +input_tensor, sample_rate = torchaudio.load(wav_file) +input_tensor = input_tensor.mean(0) +res = model.generate(input=[input_tensor], batch_size_s=300, is_final=True) + + +# example3 +import soundfile + +wav_file = os.path.join(model.model_path, "example/asr_example.wav") +speech, sample_rate = soundfile.read(wav_file) +res = model.generate(input=[speech], batch_size_s=300, is_final=True) +""" -- Gitblit v1.9.1