There are 3 ways to use PaddleSpeech
. According to the degree of difficulty, the 3 ways can be divided into Easy, Medium and Hard.
If you are newer to PaddleSpeech
and want to experience it easily without your own machine. We recommend you to use AI Studio to experience it. There is a step-by-step tutorial for PaddleSpeech
and you can use the basic function of PaddleSpeech
with a free machine.
- Python >= 3.7
- PaddlePaddle latest version (please refer to the Installation Guide)
- Only Linux is supported
- Hip: Do not use command
sh
instead of commandbash
If you want to install paddlespeech
on your own machine. There are 3 steps you need to do.
Conda is a management system of the environment. You can go to minicoda to select a version (py>=3.7) and install it by yourself or you can use the following command:
# download the miniconda
wget https://repo.continuum.io/miniconda/Miniconda3-latest-Linux-x86_64.sh
# install the miniconda
bash Miniconda3-latest-Linux-x86_64.sh -b
# conda init
$HOME/miniconda3/bin/conda init
# activate the conda
bash
Then you can create an conda virtual environment using the following command:
conda create -y -p tools/venv python=3.7
Activate the conda virtual environment:
conda activate tools/venv
Install conda dependencies for paddlespeech
:
conda install -y -c conda-forge sox libsndfile swig bzip2
Do not forget to install gcc
and gxx
on your system.
If you use linux, you can use the script below to install them.
(Hip: Do not use this script if you want to install by Hard way):
conda install -y -c gcc_linux-64=8.4.0 gxx_linux-64=8.4.0
For example, for CUDA 10.2, CuDNN7.5 install paddle 2.2.0:
python3 -m pip install paddlepaddle-gpu==2.2.0
To install paddlespeech
, there are two methods. You can use the following command:
pip install paddlespeech
If you install paddlespeech
by pip
, you can use it to help you build your model. However, you can not use the ready-made
examples in paddlespeech.
If you want to use theready-made
examples in paddlespeech
, you need to clone this repository and install paddlespeech
by the following commands:
https://github.com/PaddlePaddle/PaddleSpeech.git
cd PaddleSpeech
pip install .
- choice 1: working with
Ubuntu
Docker Container. - choice 2: working on
Ubuntu
withroot
privilege.
To avoid the trouble of environment setup, running in Docker container is highly recommended. Otherwise, if you work on Ubuntu
with root
privilege, you can skip the next step.
Docker is an open-source tool to build, ship, and run distributed applications in an isolated environment. A Docker image for this project has been provided in hub.docker.com with all the dependencies installed. This Docker image requires the support of NVIDIA GPU, so please make sure its availability and the nvidia-docker has been installed.
Take several steps to launch the Docker image:
- Download the Docker image
For example, pull paddle 2.2.0 image:
nvidia-docker pull registry.baidubce.com/paddlepaddle/paddle:2.2.0-gpu-cuda10.2-cudnn7
- Clone this repository
git clone https://github.com/PaddlePaddle/PaddleSpeech.git
- Run the Docker image
sudo nvidia-docker run --net=host --ipc=host --rm -it -v $(pwd)/PaddleSpeech:/PaddleSpeech registry.baidubce.com/paddlepaddle/paddle:2.2.0-gpu-cuda10.2-cudnn7 /bin/bash
Now you can execute training, inference and hyper-parameters tuning in Docker container.
- Clone this repository
git clone https://github.com/PaddlePaddle/PaddleSpeech.git
Install paddle 2.2.0:
python3 -m pip install paddlepaddle-gpu==2.2.0
# download and install the miniconda
pushd tools
bash extras/install_miniconda.sh
popd
# use the "bash" command to make the conda environment works
bash
# create an conda virtual environment
conda create -y -p tools/venv python=3.7
# Activate the conda virtual environment:
conda activate tools/venv
# Install the conda packags
conda install -y -c conda-forge sox libsndfile swig bzip2 libflac bc
For example, for CUDA 10.2, CuDNN7.5 install paddle 2.2.0:
python3 -m pip install paddlepaddle-gpu==2.2.0
pip install -e .[develop]
pushd tools
bash extras/install_openblas.sh
bash extras/install_kaldi.sh
popd
- Make sure these libraries or tools in dependencies installed. More information please see:
setup.py
andtools/Makefile
. - The version of
swig
should >= 3.0 - we will simplify the install process in the future.