From 1596f6f414f6f41da66506debb1dff19fffeb3ec Mon Sep 17 00:00:00 2001 From: 游雁 <zhifu.gzf@alibaba-inc.com> Date: 星期一, 24 六月 2024 11:55:17 +0800 Subject: [PATCH] fixbug hotwords --- examples/industrial_data_pretraining/seaco_paraformer/demo.py | 32 +++++++++++++++----------------- 1 files changed, 15 insertions(+), 17 deletions(-) diff --git a/examples/industrial_data_pretraining/seaco_paraformer/demo.py b/examples/industrial_data_pretraining/seaco_paraformer/demo.py index 69e9020..a88e880 100644 --- a/examples/industrial_data_pretraining/seaco_paraformer/demo.py +++ b/examples/industrial_data_pretraining/seaco_paraformer/demo.py @@ -5,28 +5,26 @@ from funasr import AutoModel -model = AutoModel(model="iic/speech_seaco_paraformer_large_asr_nat-zh-cn-16k-common-vocab8404-pytorch", - model_revision="v2.0.4", - # vad_model="iic/speech_fsmn_vad_zh-cn-16k-common-pytorch", - # vad_model_revision="v2.0.4", - # punc_model="iic/punc_ct-transformer_zh-cn-common-vocab272727-pytorch", - # punc_model_revision="v2.0.4", - # spk_model="iic/speech_campplus_sv_zh-cn_16k-common", - # spk_model_revision="v2.0.2", - ) +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", +) # 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 - ) +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 @@ -43,4 +41,4 @@ 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