*DeepSpeech2 on PaddlePaddle* is an open-source implementation of end-to-end Automatic Speech Recognition (ASR) engine, based on [Baidu's Deep Speech 2 paper](http://proceedings.mlr.press/v48/amodei16.pdf), with [PaddlePaddle](https://github.com/PaddlePaddle/Paddle) platform. Our vision is to empower both industrial application and academic research on speech recognition, via an easy-to-use, efficient and scalable implementation, including training, inference & testing module, distributed [PaddleCloud](https://github.com/PaddlePaddle/cloud) training, and demo deployment. Besides, several pre-trained models for both English and Mandarin are also released.
-[Training for Mandarin Language](#training-for-mandarin-language)
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-[Experiments and Benchmarks](#experiments-and-benchmarks)
-[Questions and Help](#questions-and-help)
## Prerequisites
- Python 2.7 only supported
- PaddlePaddle the latest version (please refer to the [Installation Guide](https://github.com/PaddlePaddle/Paddle#installation))
## Installation
Please make sure the above [prerequisites](#prerequisites) have been satisfied before moving on.
To avoid the trouble of environment setup, [running in docker container](#Running-in-Docker-Container) is highly recommended. Otherwise follow the guidelines below to install the dependencies manually.
### Prerequisites
- Python 2.7 only supported
- PaddlePaddle the latest version (please refer to the [Installation Guide](https://github.com/PaddlePaddle/Paddle#installation))
Docker is an open 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](https://hub.docker.com) with all the dependencies installed, including the pre-built PaddlePaddle, CTC decoders, and other necessary Python and third-party packages. This Docker image requires the support of NVIDIA GPU, so please make sure its availiability and the [nvidia-docker](https://github.com/NVIDIA/nvidia-docker) has been installed.
sudo nvidia-docker run -it-v$(pwd)/models:/models paddlepaddle/models:deep-speech-2 /bin/bash
```
Now go back and start from the [Getting Started](#getting-started) section, you can execute training, inference and hyper-parameters tuning similary in the Docker container.