mirror of
https://github.com/modelscope/FunASR
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20 lines
1.2 KiB
Python
20 lines
1.2 KiB
Python
from funasr_torch import Paraformer
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#model_dir = "/Users/shixian/code/funasr/export/damo/speech_paraformer-large-vad-punc_asr_nat-zh-cn-16k-common-vocab8404-pytorch"
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model_dir = "/Users/shixian/code/funasr/export/damo/speech_paraformer-large_asr_nat-zh-cn-16k-common-vocab8404-pytorch"
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model = Paraformer(model_dir, batch_size=2)
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# when using paraformer-tiny-commandword_asr_nat-zh-cn-16k-vocab544-pytorch, you should set pred_bias=0
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# plot_timestamp_to works only when using speech_paraformer-large-vad-punc_asr_nat-zh-cn-16k-common-vocab8404-pytorch
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# model_dir = "/Users/shixian/code/funasr/export/damo/speech_paraformer-tiny-commandword_asr_nat-zh-cn-16k-vocab544-pytorch"
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# model = Paraformer(model_dir, batch_size=2, pred_bias=0)
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# when using paraformer-large-vad-punc model, you can set plot_timestamp_to="./xx.png" to get figure of alignment besides timestamps
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# model_dir = "/Users/shixian/code/funasr/export/damo/speech_paraformer-large-vad-punc_asr_nat-zh-cn-16k-common-vocab8404-pytorch"
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# model = Paraformer(model_dir, batch_size=1)
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# model = Paraformer(model_dir, batch_size=1, plot_timestamp_to="test.png")
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wav_path = "YourPath/xx.wav"
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result = model(wav_path)
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print(result) |