Update README.md

README.md

@@ -24,6 +24,11 @@ Two versions of pretrained W2V2 models are available:
 - **LB1100/checkpoint_best.pt** pretrained using 1100-hour of LB home recordings collected from 110 families of children under 5-year-old
 - **LL4300/checkpoint_best.pt** pretrained using 1100-hour of LB home recordings collected from 110 families + 3200-hour of LENA home recordings from 275 families of children under 5-year-old
 
+Two pretrained ECAPA-TDNN speaker embeddings are available:
+- **ECAPA_TDNN_LB/embedding_model.ckpt** pretrained using 12-hour of labeled LB home recordings collected from 22 families of infants under 14-month-old
+- **ECAPA_TDNN_LB_LENA/embedding_model.ckpt** pretrained using 12-hour of labeled LB home recordings collected from 22 families + 18-hour of labeled LENA home recordings from 30 families of infants under 14-month-old
+
+
 ## Model Sources
 For more information regarding this model, please checkout our paper
 - **Paper [optional]:** [More Information Needed]
@@ -37,7 +42,7 @@ We develop our complete fine-tuning recipe using SpeechBrain toolkit available a
 ## Quick Start
 
 <!-- This section is for the model use when fine-tuned for a task, or when plugged into a larger ecosystem/app -->
-If you wish to use fairseq framework, the following code snippet provides two functions of loading our pretrained model and extracting W2V2 features. 
+If you wish to use fairseq framework, the following code snippet provides two functions of loading our pretrained W2V2 model and extracting features. 
 
   <pre><code>
   import torch