Speech recognition is the ability of a computer software to identify words and phrases in spoken language and convert them to human readable text. In this tutorial, we will use SpeechRecognition Python library to do that.
First, let's install the library:
pip3 install speech_recognition
Okey, open up a new Python file and follow along:
import speech_recognition as sr
The nice thing about this library is it supports several recognition engines:
We gonna use Google Speech Recognition here, as it doesn't require any API key.
Make sure you have an audio file in the current directory that contains english speech:
filename = "16-122828-0002.wav"
This file was grabbed from LibriSpeech dataset, but you can bring anything you want, just change the name of the file, let's initialize our speech recognizer:
# initialize the recognizer r = sr.Recognizer()
The below code is responsible for loading the audio file, and converting the speech into text using Google Speech Recognition:
# open the file with sr.AudioFile(filename) as source: # listen for the data (load audio to memory) audio_data = r.record(source) # recognize (convert from speech to text) text = r.recognize_google(audio_data) print(text)
This will take few seconds to finish, as it uploads the file to Google and grabs the output, here is my result:
I believe you're just talking nonsense
Now let's use our microphone to convert our speech:
with sr.Microphone() as source: # read the audio data from the default microphone audio_data = r.record(source, duration=5) print("Recognizing...") # convert speech to text text = r.recognize_google(audio_data) print(text)
This will hear from your microphone for 5 seconds and then tries to convert that speech into text !
It is pretty similar to the previous code, but we are using Microphone() object here to read the audio from the default microphone, and then we used duration parameter in record() function to stop reading after 5 seconds and then uploads the audio data to Google to get the output text.
You can also use offset parameter in record() function to start recording after offset seconds.
Also, you can recognize different languages by passing language parameter to recognize_google() function. For instance, if you want to recognize spanish speech, you would use:
text = r.recognize_google(audio_data, language="es-ES")
Check out supported languages in this stackoverflow answer.
As you can see, it is pretty easy and simple to use this library for converting speech to text. This library is widely used out there in the wild, make sure you master it, check their official documentation.
Happy Coding ♥View Full Code