Multiple Speakers 2
Deciphering between multiple speakers in one audio file is called speaker diarization. However, you've seen the free function we've been using, recognize_google() doesn't have the ability to transcribe different speakers.
One way around this, without using one of the paid speech to text services, is to ensure your audio files are single speaker.
This means if you were working with phone call data, you would make sure the caller and receiver are recorded separately. Then you could transcribe each file individually.
In this exercise, we'll transcribe each of the speakers in our multiple speakers audio file individually.
This is a part of the course
“Spoken Language Processing in Python”
Exercise instructions
- Pass
speakersto theenumerate()function to loop through the different speakers. - Call
record()onrecognizerto convert theAudioFiles intoAudioData. - Use
recognize_google()to transcribe each of thespeaker_audioobjects.
Hands-on interactive exercise
Have a go at this exercise by completing this sample code.
recognizer = sr.Recognizer()
# Multiple speakers on different files
speakers = [sr.AudioFile("speaker_0.wav"),
sr.AudioFile("speaker_1.wav"),
sr.AudioFile("speaker_2.wav")]
# Transcribe each speaker individually
for i, speaker in enumerate(____):
with speaker as source:
speaker_audio = recognizer.____(source)
print(f"Text from speaker {i}:")
print(recognizer.____(____,
language="en-US"))This exercise is part of the course
Spoken Language Processing in Python
Learn how to load, transform, and transcribe speech from raw audio files in Python.
Speech recognition is still far from perfect. But the SpeechRecognition library provides an easy way to interact with many speech-to-text APIs. In this section, you'll learn how to use the SpeechRecognition library to easily start converting the spoken language in your audio files to text.
Exercise 1: SpeechRecognition Python libraryExercise 2: Pick the wrong speech_recognition APIExercise 3: Using the SpeechRecognition libraryExercise 4: Using the Recognizer classExercise 5: Reading audio files with SpeechRecognitionExercise 6: From AudioFile to AudioDataExercise 7: Recording the audio we needExercise 8: Dealing with different kinds of audioExercise 9: Different kinds of audioExercise 10: Multiple Speakers 1Exercise 11: Multiple Speakers 2Exercise 12: Working with noisy audioWhat is DataCamp?
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