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PaddleSpeech
mirror of https://github.com/PaddlePaddle/PaddleSpeech
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PaddleSpeech/deploy
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yangyaming 3ee020397c
Refactor scorer and move utility functions to decoder_util.h 		7 years ago
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README.md Refactor scorer and move utility functions to decoder_util.h 7 years ago
__init__.py change probs' computation into log scale & add best path decoder 8 years ago
ctc_decoders.cpp Refactor scorer and move utility functions to decoder_util.h 7 years ago
ctc_decoders.h reorganize cpp files 7 years ago
decoder_utils.cpp Refactor scorer and move utility functions to decoder_util.h 7 years ago
decoder_utils.h Refactor scorer and move utility functions to decoder_util.h 7 years ago
decoders.i Refactor scorer and move utility functions to decoder_util.h 7 years ago
scorer.cpp Refactor scorer and move utility functions to decoder_util.h 7 years ago
scorer.h Refactor scorer and move utility functions to decoder_util.h 7 years ago
setup.py refine wrapper for swig and simplify setup 7 years ago
swig_decoders_wrapper.py refine wrapper for swig and simplify setup 7 years ago

README.md

Installation

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

git clone https://github.com/kpu/kenlm.git
wget http://www.openfst.org/twiki/pub/FST/FstDownload/openfst-1.6.3.tar.gz
tar -xzvf openfst-1.6.3.tar.gz

Compiling for python interface requires swig, please make sure swig being installed.

Then run the setup

python setup.py install
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