Update README.md

README.md

@@ -11,11 +11,13 @@ pipeline_tag: audio-classification
 
 <!-- Provide a quick summary of what the model is/does. -->
 
-We explore benefits of unsupervised pretraining of wav2vec 2.0 (W2V2) using large-scale unlabeled home recordings collected using LittleBeats and LENA (Language Environment Analysis) devices.
-LittleBeats (LB) is a new infant wearable multi-modal device that we developed, which simultaneously records audio, movement of the infant, as well as heart-rate variablity.
+We explore benefits of unsupervised pretraining of wav2vec 2.0 (W2V2) using large-scale unlabeled home recordings collected using LittleBeats (LB) and LENA (Language Environment Analysis) devices.
+LittleBeats is a new infant wearable multi-modal device that we developed, which simultaneously records audio, movement of the infant, as well as heart-rate variablity.
 We use W2V2 to advance LB audio pipeline such that it automatically provides reliable labels of speaker diarization and vocalization classifications for family members, including infants, parents, and siblings, at home. 
 We show that W2V2 pretrained on thousands hours of large-scale unlabeled home audio outperforms oracle W2V2 pretrained on 52k-hours released by Facebook/Meta in terms of automatic family audio analysis tasks.
 
+For more details about LittleBeats, check out **https://littlebeats.hdfs.illinois.edu/**
+
 ## Model Description
 
 <!-- Provide a longer summary of what this model is. -->