Xinghai Sun
cd3617aeb4
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8 years ago | |
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data_utils | 8 years ago | |
datasets | 8 years ago | |
README.md | 8 years ago | |
compute_mean_std.py | 8 years ago | |
decoder.py | 8 years ago | |
infer.py | 8 years ago | |
model.py | 8 years ago | |
requirements.txt | 8 years ago | |
train.py | 8 years ago |
README.md
Deep Speech 2 on PaddlePaddle
Installation
Please replace $PADDLE_INSTALL_DIR
with your own paddle installation directory.
pip install -r requirements.txt
export LD_LIBRARY_PATH=$PADDLE_INSTALL_DIR/Paddle/third_party/install/warpctc/lib:$LD_LIBRARY_PATH
For some machines, we also need to install libsndfile1. Details to be added.
Usage
Preparing Data
cd data
python librispeech.py
cat manifest.libri.train-* > manifest.libri.train-all
cd ..
After running librispeech.py, we have several "manifest" json files named with a prefix manifest.libri.
. A manifest file summarizes a speech data set, with each line containing the meta data (i.e. audio filepath, transcription text, audio duration) of each audio file within the data set, in json format.
By cat manifest.libri.train-* > manifest.libri.train-all
, we simply merge the three seperate sample sets of LibriSpeech (train-clean-100, train-clean-360, train-other-500) into one training set. This is a simple way for merging different data sets.
More help for arguments:
python librispeech.py --help
Traininig
For GPU Training:
CUDA_VISIBLE_DEVICES=0,1,2,3 python train.py --trainer_count 4 --train_manifest_path ./data/manifest.libri.train-all
For CPU Training:
python train.py --trainer_count 8 --use_gpu False -- train_manifest_path ./data/manifest.libri.train-all
More help for arguments:
python train.py --help
Inferencing
python infer.py
More help for arguments:
python infer.py --help