How to convert Speech-to-Text with Python?

This page summarizes the projects mentioned and recommended in the original post on dev.to

Our great sponsors
  • InfluxDB - Build time-series-based applications quickly and at scale.
  • SonarLint - Clean code begins in your IDE with SonarLint
  • talent.io - Download talent.io’s Tech Salary Report
  • Scout APM - Truly a developer’s best friend
  • wav2letter

    Facebook AI Research's Automatic Speech Recognition Toolkit

    Flashlight is a fast, flexible machine learning library written entirely in C++ from the Facebook AI Research Speech team and the creators of Torch and Deep Speech. Flashlight's ASR application (formerly the wav2letter project) provides training and inference capabilities for end-to-end speech recognition systems. This engine is really performant but you will need to compile all the C++ libraries before using it with Python.

  • examples

    TensorFlow examples (by tensorflow)

    DeepSpeech is an open-source Speech-To-Text engine, using a model trained by machine learning techniques based on Baidu's Deep Speech research paper. Project DeepSpeech uses Google's TensorFlow to make the implementation easier.

  • InfluxDB

    Build time-series-based applications quickly and at scale.. InfluxDB is the Time Series Data Platform where developers build real-time applications for analytics, IoT and cloud-native services in less time with less code.

NOTE: The number of mentions on this list indicates mentions on common posts plus user suggested alternatives. Hence, a higher number means a more popular project.

Suggest a related project

Related posts