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README.md

@@ -86,7 +86,7 @@ python3 km.py   --train_file files/filesTrainWAV.txt   --val_file files/filesVal
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 ## 2. A help to chose the k number for K-Means clustering
-### • Method with taking in considar of the distance of the last fusion. The files the are placed in the Segmentfeatures folder represent the output of the segmentation of [SD-HuBERT : Sentence-Level Self-Distillation Induces Syllabic Organization in HuBERT](https://github.com/cheoljun95/sdhubert) or [Sylber : Syllabic Embedding Representation of Speech from Raw Audio](https://github.com/Berkeley-Speech-Group/sylber)
+### • Method with taking in considar of the distance of the last fusion. The files the are placed in the Segmentfeatures folder represent the output (average feature per segment) of the segmentation of [SD-HuBERT : Sentence-Level Self-Distillation Induces Syllabic Organization in HuBERT](https://github.com/cheoljun95/sdhubert) or [Sylber : Syllabic Embedding Representation of Speech from Raw Audio](https://github.com/Berkeley-Speech-Group/sylber)
 **hierarchiqueSansDerniereDistance.py :** This method uses the average and the complete linkage.
 
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