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docs(readme): add EspNet for Speech Processing Tasks

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@ -131,6 +131,7 @@ Further resources:
- [Federated Learning](#python-federated-learning) - [Federated Learning](#python-federated-learning)
- [Kaggle Competition Source Code](#python-kaggle-competition-source-code) - [Kaggle Competition Source Code](#python-kaggle-competition-source-code)
- [Reinforcement Learning](#python-reinforcement-learning) - [Reinforcement Learning](#python-reinforcement-learning)
- [Speech Recognition](#python-speech-recognition)
- [Ruby](#ruby) - [Ruby](#ruby)
- [Natural Language Processing](#ruby-natural-language-processing) - [Natural Language Processing](#ruby-natural-language-processing)
- [General-Purpose Machine Learning](#ruby-general-purpose-machine-learning) - [General-Purpose Machine Learning](#ruby-general-purpose-machine-learning)
@ -1474,6 +1475,10 @@ be
* [RLlib](https://github.com/ray-project/ray) - RLlib is an industry level, highly scalable RL library for tf and torch, based on Ray. It's used by companies like Amazon and Microsoft to solve real-world decision making problems at scale. * [RLlib](https://github.com/ray-project/ray) - RLlib is an industry level, highly scalable RL library for tf and torch, based on Ray. It's used by companies like Amazon and Microsoft to solve real-world decision making problems at scale.
* [DI-engine](https://github.com/opendilab/DI-engine) - DI-engine is a generalized Decision Intelligence engine. It supports most basic deep reinforcement learning (DRL) algorithms, such as DQN, PPO, SAC, and domain-specific algorithms like QMIX in multi-agent RL, GAIL in inverse RL, and RND in exploration problems. * [DI-engine](https://github.com/opendilab/DI-engine) - DI-engine is a generalized Decision Intelligence engine. It supports most basic deep reinforcement learning (DRL) algorithms, such as DQN, PPO, SAC, and domain-specific algorithms like QMIX in multi-agent RL, GAIL in inverse RL, and RND in exploration problems.
<a name="python-speech-recognition"></a>
#### Speech Recognition
* [EspNet](https://github.com/espnet/espnet) - ESPnet is an end-to-end speech processing toolkit covering end-to-end speech recognition, text-to-speech, speech translation, speech enhancement, speaker diarization, spoken language understanding, and so on. ESPnet uses pytorch as a deep learning engine and also follows Kaldi style data processing, feature extraction/format, and recipes to provide a complete setup for various speech processing experiments.
<a name="ruby"></a> <a name="ruby"></a>
## Ruby ## Ruby