DeepSpeech – TensorFlow implementation of Baidu’s DeepSpeech architecture

DeepSpeech is an open source Speech-To-Text engine, using a model trained by machine learning techniques. It’s a TensorFlow implementation of Baidu’s DeepSpeech architecture.

This open-source platform is designed for advanced decoding with flexible knowledge integration.

The software is in an early stage of development.

The core of the system is a bidirectional recurrent neural network (BRNN) trained to ingest speech spectrograms and generate English text transcriptions. A pre-trained English model is available for use.

The software needs Python 2.7, and the Git Large File Storage – a Git extension for versioning large files.

Features include:

  • 3 different ways to use the software:
    • Python package.
    • Command-line client.
    • Node.JS package.
  • Works with signed 16-bit PCM data.
  • Takes word lattice as input, perform feature extraction specified by developers, generate factor graphs based on descriptive rules, and perform learning and inference automatically.

Supported operating systems:

  • OS X 10.10, 10.11, 10.12 and 10.13
  • Linux x86 64 bit with a modern CPU (needs at least AVX/FMA)
  • Linux x86 64 bit with a modern CPU + NVIDIA GPU (Compute Capability at least 3)
  • Raspbian Jessie on Raspberry Pi 3

Website: github.com/mozilla/DeepSpeech
Support: Releases
Developer: Mozilla
License: Mozilla Public License 2.0

DeepSpeech is written in C++ and Python. Learn C++ with our recommended free books and free tutorials. Learn Python with our recommended free books and free tutorials.

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