Speaker diarization
This pull request **introduces 1 alert** when merging b6411e54d856fbe4193e259784afa2e08af516c5 into 941ef1fd71bd2515a4ba7092d65146edfddc1229 - [view on LGTM.com](https://lgtm.com/projects/g/NVIDIA/NeMo/rev/pr-9e7b6190b88049553be6394e4585e7cfbe3807f2)

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This PR enables speaker diarization inference capability in NeMo. It features and supports both oracle and non-oracle VAD diarization with spectral clustering. 

Here are some of the new additions made:

- Adds support to diarize wav files given through list or from a file containing paths to audio files (speaker_diarize.py)
- Added ClusteringDiarizer model that combines VAD and Speaker Embeddings model to extract time stamps and Embeddings (clustering_diarizer.py)
- Added VAD utils to support overlap segment creation and probability smoothing for combining VAD decisions (vad_utils.py)
- Added script to get best thresholds for unseen data given through dev manifest. (vad_tune_threshold.py) 
- Added utils to clean and combine time stamps from VAD. (speaker_utils.py)
- Perform clustering and writes predicted rttm (speaker_utils.py)
- Added rttm_to_manifest.py to create oracle manifest for performing diarization with any external VAD decision 