| Speaker tasks in general are broadly classified into two tasks: | |
| - [Speaker Recognition](https://docs.nvidia.com/deeplearning/nemo/user-guide/docs/en/main/asr/speaker_recognition/intro.html) | |
| - [Speaker Diarization](https://docs.nvidia.com/deeplearning/nemo/user-guide/docs/en/main/asr/speaker_diarization/intro.html) | |
| **Speaker Recognition** is a research area which solves two major tasks: speaker identification (what is the identity of the speaker?) and speaker verification (is the speaker who they claim to be?). where as **Speaker Diarization** is a task segmenting audio recordings by speaker labels (Who Speaks When?). | |
| In *recognition* folder we provide scripts for training, inference and verification of audio samples. | |
| In *diarization* folder we provide scripts for inference of speaker diarization using pretrained VAD (optional) and Speaker embedding extractor models | |