Updating x-vector readme to add diarization recipe link

README.md

@@ -27,7 +27,7 @@ widget:
 <iframe src="https://ghbtns.com/github-btn.html?user=speechbrain&repo=speechbrain&type=star&count=true&size=large&v=2" frameborder="0" scrolling="0" width="170" height="30" title="GitHub"></iframe>
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-# Speaker Verification with xvector embeddings on Voxceleb
+# Speaker Verification with x-vector embeddings on Voxceleb
 
 This repository provides all the necessary tools to extract speaker embeddings with a pretrained TDNN model using SpeechBrain. 
 The system is trained on Voxceleb 1+ Voxceleb2 training data. 
@@ -92,10 +92,19 @@ python train_speaker_embeddings.py hparams/train_x_vectors.yaml --data_folder=yo
 
 You can find our training results (models, logs, etc) [here](https://drive.google.com/drive/folders/1RtCBJ3O8iOCkFrJItCKT9oL-Q1MNCwMH?usp=sharing).
 
+# Speaker Diarization with ECAPA-TDNN Embeddings
+Note that, this trained x-vector model is also used for speaker diarization task. A full diarization pipeline including boudary preparation using RTTM files, speaker embedding extraction, and backend spectral clustering for [AMI dataset](https://groups.inf.ed.ac.uk/ami/corpus/) can be found [here](https://github.com/speechbrain/speechbrain/tree/develop/recipes/AMI/Diarization).
+
+1. Run Inference for Diarization:
+```
+cd  recipes/AMI/Diarization
+python experiment.py hparams/xvectors.yaml
+```
+
 ### Limitations
 The SpeechBrain team does not provide any warranty on the performance achieved by this model when used on other datasets.
 
-#### Referencing xvectors
+#### Referencing x-vectors
 ```@inproceedings{DBLP:conf/odyssey/SnyderGMSPK18,
   author    = {David Snyder and
                Daniel Garcia{-}Romero and