Speaker Diarization Frameworks in Python: Tutorial and Code Walkthrough

Speaker diarization identifies and separates different speakers in an audio file. Think of it as automatically labeling "Speaker A spoke from 0:00-0:15, Speaker B spoke from 0:15-0:30" throughout your recording.

, podcast editing, for speaker diarization is

straightforward. Follow these steps:

• Install the pyannote.audio package using pip:
  

pip3 install pyannote.audio

• Obtain your authentication token to download pretrained models by visiting , follow these steps:

  
  
  
  
  
  • Install dependencies:
    
  
  
  
  
  
  

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  apt-get update && apt-get install -y libsndfile1 ffmpeg
  
  pip3 install Cython
  
  

  
  
  
  
  
  
  
  
  
  • Install NeMo:
    
  
  
  
  
  
  

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  pip install git+https://github.com/NVIDIA/[email protected]#egg=nemo_toolkit[all]
  
  

  
  
  
  
  
  
  
  
  

  • Download the config file for the inference from the file.

    
    

    
    
    
    3. Simple Diarizer
    

    
    
    

    . To get started with simple_diarizer, follow these steps:

    
    
    
    
    
    • Install the package using pip:
      
    
    
    
    
    
    

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    pip install simple_diarizer
    
    

    
    
    
    
    
    
    
    
    
    • Define a Diarizer object:
      
    
    
    
    
    
    

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    from simple_diarizer.diarizer import Diarizer
    
    
    
    diarization = Diarizer(embed_model='xvec', cluster_method='sc')
    
    

    
    
    
    
    
    
    
    
    
    • Perform speaker diarization on an audio file by either passing the number of speakers:
      
    
    
    
    
    
    

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    # Replace "${AUDIO_FILE_PATH}" with the path to your audio file
    
    segments = diarization.diarize("${AUDIO_FILE_PATH}", num_speakers=NUM_SPEAKERS)
    
    

    
    
    
    
    
    
    

    Or by passing a threshold value:
    
    

    
    
    
    
    

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    segments = diarization.diarize("${AUDIO_FILE_PATH}", threshold=THRESHOLD)
    
    

    
    
    
    
    
    
    
    

    The segment variable stores the speaker information and timing details, including start and end times for each segment.

    
    
    

    
    
    
    4. Falcon Speaker Diarization
    

    
    
    

    for free and copy your AccessKey.

  
  

  • Create an instance of the engine:
    
    

  
  
  
  
  
  
  

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  import pvfalcon
  
  
  
  # Replace "${ACCESS_KEY}" with your Picovoice Console AccessKey
  
  falcon = pvfalcon.create(access_key="${ACCESS_KEY}")
  
  

  
  
  
  
  
  
  
  
  
  
  • Perform speaker diarization on an audio file:
    
  
  
  
  
  
  
  

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  # Replace "${AUDIO_FILE_PATH}" with the path to your audio file
  
  segments = falcon.process_file("${AUDIO_FILE_PATH}")
  
  for segment in segments:
  
      print(
  
          "{speaker_tag=%d start_sec=%.2f end_sec=%.2f}"
  
          % (segment.speaker_tag, segment.start_sec, segment.end_sec)
  
      )
  
  

  
  
  
  
  
  
  
  

  Each segment in the segments array includes timing information and speaker identification.

  
  
  

  For more information about Falcon Speaker Diarization, check out the .

  
  
  

  
  
  
  Video Tutorial
  

  
  
  

  
  
  

  
  
  
  
  
  

  This tutorial was originally published on Picovoice

  Vollständiger Original-Bericht

  Ausführliche Details, Code-Beispiele & Hersteller-Stellungnahme auf dev.to.

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