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GitHub - rushabhdharia/SpeechToText: Project on Automatic Speech Recogition for course Deep Learning Speech Processing
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Project on Automatic Speech Recogition for course Deep Learning Speech Processing

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SpeechToText

Project on Automatic Speech Recogition for course Deep Learning Speech Processing

Dataset Used

  1. LibriSpeech100 (100 hours) - https://www.openslr.org/12

Steps to execute code

  1. Download LibriSpeech100 Dataset from the link mentioned above.
  2. Run CreatePickleFiles.ipynb - Creates Pickle Files of the Input Data
  3. Create train_all, dev_all and test_all folders in train, dev and test folders respectively which lie inside the LibriSpeech100 folder. We will gather all our input and output files in these directories.
  4. Run GatherPickleAndTextFiles.ipynb - Gathers all the input pickle and output text files and places them in their appropriate folders
  5. Run speech2text.py on terminal or Speech2Text.ipynb in a jupyter environment

References

  1. Hori, Takaaki, Jaejin Cho, and Shinji Watanabe. "End-to-end speech recognition with word-based RNN language models." 2018 IEEE Spoken Language Technology Workshop (SLT). IEEE, 2018.
  2. https://web.stanford.edu/class/cs224s/lectures/224s.17.lec8.pdf
  3. https://arxiv.org/pdf/1803.10225.pdf

Technologies Used

  1. Miniconda
  2. Tensorflow 2 Setup Tensorflow 2 on Conda

Collaborators

Rushabh Dharia
Chaitanya Patil

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Project on Automatic Speech Recogition for course Deep Learning Speech Processing

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