Performing hands-on speech diarization

Transitioning from the theoretical context of speech diarization, let’s immerse ourselves in the practical implementation that combines WhisperX, NeMo, and other supporting Python libraries, all from the comfort of our trusty Google Colaboratory. I encourage you to visit the book’s GitHub repository, find the LOAIW_ch08_diarizing_speech_with_WhisperX_and_NVIDIA_NeMo.ipynb notebook (https://github.com/PacktPublishing/Learn-OpenAI-Whisper/blob/main/Chapter08/LOAIW_ch08_diarizing_speech_with_WhisperX_and_NVIDIA_NeMo.ipynb), and run the Python code yourself; feel free to experiment by modifying parameters and observe the results. The notebook provides a detailed walk-through to integrate Whisper’s transcription capabilities with NeMo’s diarization framework, offering a robust solution to analyze speech in audio recordings.

The notebook is structured into several key sections, each focusing on a specific aspect of the...