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Python Deep Learning Projects
book

Python Deep Learning Projects

by Matthew Lamons, Rahul Kumar, Abhishek Nagaraja
October 2018
Intermediate to advanced content levelIntermediate to advanced
472 pages
10h 57m
English
Packt Publishing
Content preview from Python Deep Learning Projects

Training the model

Now that we understand the data that we are using and the DeepSpeech model architecture, let's set up the environment to train the model. There are some preliminary steps to create a virtual environment for the project that are optional, but always recommended to use. Also, it's recommended to use GPUs to train these models.

Along with Python Version 3.5 and TensorFlow version 1.7+, the following are some of the prerequisites:

  • python-Levenshtein: To compute character error rate (CER), basically the distance
  • python_speech_features: To extract MFCC features from raw data
  • pysoundfile: To read FLAC files
  • scipy: Helper functions for windowing
  • tqdm: For displaying a progress bar

Let's create the virtual environment and install ...

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Publisher Resources

ISBN: 9781788997096Supplemental Content