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PaddleSpeech
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PaddleSpeech/deploy
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Yibing Liu 37b236869f
Delete swig_decoder.py 		8 years ago
..
README.md add setup and README for deployment 8 years ago
__init__.py change probs' computation into log scale & add best path decoder 8 years ago
ctc_decoders.cpp refine the interface of decoders in swig 8 years ago
ctc_decoders.h refine the interface of decoders in swig 8 years ago
ctc_decoders.i refine the interface of decoders in swig 8 years ago
decoder_setup.py refine the interface of decoders in swig 8 years ago
scorer.cpp refine the interface of decoders in swig 8 years ago
scorer.h refine the interface of decoders in swig 8 years ago
scorer.i add initial files for deployment 8 years ago
scorer_setup.py code cleanup for the deployment decoder 8 years ago
setup.sh enable loading language model in multiple format 8 years ago
swig_decoders.py refine the interface of decoders in swig 8 years ago

README.md

Installation

The setup of the decoder for deployment depends on the source code of kenlm, first clone it to current directory (i.e., deep_speech_2/deploy)

git clone https://github.com/kpu/kenlm.git

Then run the setup

sh setup.sh

After the installation succeeds, go back to the parent directory

cd ..

Deployment

For GPU deployment

CUDA_VISIBLE_DEVICES=0 python deploy.py

For CPU deployment

python deploy.py --use_gpu=False

More help for arguments

python deploy.py --help