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RNN CTC by using TensorFlow.
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ugnelis Merge pull request #16 from ugnelis/multi-layers-fix
Fixed multi layers issue. Now it's possible to have multiple layers.
Latest commit 8fc5457 Jan 30, 2018
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data/LibriSpeech Added example data. Added text file and audio file reading. Sep 28, 2017
.travis.yml Add initial test, fix update travis config Oct 12, 2017
LICENSE Added license. Oct 2, 2017
requirements.txt add requirements.txt Oct 4, 2017

TensorFlow RNN CTC Build Status

Connectionist Temporal Classification (CTC) by using Recurrent Neural Network (RNN) in TensorFlow.


  • Python 2.7+ (for Linux)
  • Python 3.5+ (for Windows)
  • TensorFlow 1.0+
  • NumPy 1.5+
  • SciPy 0.12+
  • python_speech_features 0.1+


I suggest you to use Anaconda. For TensorFlow and python_speech_features use pip:

$ activate anaconda_env_name
(anaconda_env_name)$ pip install python_speech_features
(anaconda_env_name)$ pip install --ignore-installed --upgrade tensorflow # without GPU
(anaconda_env_name)$ pip install --ignore-installed --upgrade tensorflow-gpu # with GPU


Run training by using file.



This project is licensed under the terms of the MIT license.

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