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Speech Recognition with Python: Comparing 9 most prominent alternatives

Satish Chandra Gupta
Machine Learning Practitioner. I learn & write about doing ML in production. Cofounder: SlangLabs.in. Ex: Amazon, Microsoft Research. Newsletter: ML4Devs.com
Originally published at slanglabs.in on ・1 min read

Learn which of the 9 most prominent automatic speech recognition engines is best for your needs, and how to use it in Python programs.


Automated Speech Recognition (ASR) is the necessary first step in processing voice. In ASR, an audio file or speech spoken to a microphone is processed and converted to text, therefore it is also known as Speech-to-Text (STT). Then this text is fed to a Natural Language Processing/Understanding (NLP/NLU) to understand and extract key information (such as intentions, sentiments), and then appropriate action is taken. There are also stand-alone applications of ASR, e.g. transcribing dictation, or producing real-time subtitles for videos.

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