Install SpeechRecognition $ pip install SpeechRecognition After Installation, verify the version >>> import speech_recognition as sr >>> sr.__version__ '3.8.1' Recognizer Class in SpeechRecognition Key Implementations done by SpeechRecognition using the Recognizer class. Primary purpose of Recognizer instance is to recognize speech. Each instance comes with a variety of settings and functionality for recognizing speech from an audio source. Creating a Recognizer instance is easy. In your current interpreter session, just type: >>> r = sr.Recognizer() Methods for Recognizing Speech Each Recognizer instance has seven methods for recognizing speech from an audio source using various APIs recognize_bing(): Microsoft Bing Speech recognize_google(): Google Web Speech API recognize_google_cloud(): Google Cloud Speech - requires installation of the google-cloud-speech package recognize_houndify(): Houndify by SoundHound recognize_ibm(): IBM Speech to Text recognize_sphinx(): CMU Sphinx - requires installing PocketSphinx recognize_wit(): Wit.ai Of the seven, only recognize_sphinx() works offline with the CMU Sphinx engine. The other six all require an internet connection. Recognizing Speech Each recognize_*() method will throw a speech_recognition.RequestError exception if the API is unreachable. For recognize_sphinx(), this could happen as the result of a missing, corrupt or incompatible Sphinx installation. For the other six methods, RequestError may be thrown if quota limits are met, the server is unavailable, or there is no internet connection. Call recognize_google() >>> r.recognize_google() Adding Audio Files for Speech Recognition Now, record the WAV File so that it can be translated to text. Any WAV file can be taken Speech Extraction Google API speech_recognition sr harvard=sr.AudioFile( ) r = sr.Recognizer() harvard source: audio=r.record(source) (type(audio)) (r.recognize_google(audio)) import as 'myrecord.wav' with as print print The text will be recognized from audio file "myaudio.wav" and will be printed