Google speech to text api how to#

# Importing the speech_recognition library import speech_recognition as sr # Create an instance of the Recognizer class recognizer = sr.Recognizer() # Set the energy threshold recognizer.energy_threshold = 300 # Convert audio to AudioFile clean_support_call = sr.AudioFile('staytuned.wav') # Convert AudioFile to AudioData with clean_support_call as source: clean_support_call_audio = recognizer.record(source) # Transcribe AudioData to text text = recognizer.recognize_google(clean_support_call_audio, language='en-US') print(text)Īnd the output we get is: hello everybody today we are going to talk about speech-to-text stay tuned Speech to Text with Noisy Audio Note that the recognize_google allows 50 free calls per day. wav file that we are going to use for this example can be found here. Snowboy Hotword Detection (works offline)įor our example we will use the recognize_google, however there are also some other choices like recognize_bing(), recognize_wit().Microsoft Bing Voice Recognition (Deprecated).

SpeechRecognition is a library for performing speech recognition, with support for several engines and APIs, online and offline.

Google speech to text api how to#

In this post, we will show how to use the Python SpeechRecognition library to easily start converting the spoken language in our audio files to text. However, the SpeechRecognition library provides an easy way to interact with many speech-to-text APIs.

Speech recognition (or Speech To Text) is still far from perfect.