in progress updates

README.md

@@ -13,12 +13,17 @@ pipeline_tag: audio-classification
 
 <!-- Provide a quick summary of what the model is/does. -->
 
-We build a CTC-based ASR model using wav2vec 2.0 (W2V2) for children under 4-year-old. We use two-level fine-tuning to gradually reduce age mismatch between adult ASR to child ASR.
-We first fine-tune W2V2-LibriSpeech960h using [My Science Tutor](https://boulderlearning.com/products/myst/) corpus (consists of conversational speech of students between the third and fifth grades with a virtual tutor) on character level. Then we fine-tune W2V2-MyST using [Providence](https://phonbank.talkbank.org/access/Eng-NA/Providence.html) corpus (consists of longititude audio of 6 English-speaking children aged from 1-4 years interacting with their mothers at home) on phoneme sequences or consonant/vowel sequences.  
-We show W2V2-Providence is helpful for improving children's vocalization classification task on two corpus, including [Rapid-ABC](https://openaccess.thecvf.com/content_cvpr_2013/html/Rehg_Decoding_Childrens_Social_2013_CVPR_paper.html) and [BabbleCor](https://osf.io/rz4tx/). 
+We build a CTC-based phoneme recognition model using wav2vec 2.0 (W2V2) for children under 4-year-old. We use three-level fine-tuning to gradually reduce age mismatch between adult phonetics to child phonetics.
+
+**W2V2-Libri100h**: We first fine-tune W2V2-Base pretrained on unlabeled 960h adult speech corpus with IPA phone sequences. 
+**W2V2-MyST**: We then fine-tune W2V2-Libri100h using [My Science Tutor](https://boulderlearning.com/products/myst/) corpus (consists of conversational speech of students between the third and fifth grades with a virtual tutor). 
+**W2V2-Libri100h-Pro (two-level fine-tuning)**: We fine-tune W2V2-Libri100h using [Providence](https://phonbank.talkbank.org/access/Eng-NA/Providence.html) corpus (consists of longititude audio of 6 English-speaking children aged from 1-4 years interacting with their mothers at home) on phoneme sequences.  
+**W2V2-MyST-Pro (three-level fine-tuning)**: Similar as W2V2-Libri100h-Pro, we fine-tune W2V2-MyST using Providence on phoneme sequences.  
+
+We show W2V2-MyST-Pro is helpful for improving children's vocalization classification task on two corpus, including [Rapid-ABC](https://openaccess.thecvf.com/content_cvpr_2013/html/Rehg_Decoding_Childrens_Social_2013_CVPR_paper.html) and [BabbleCor](https://osf.io/rz4tx/). 
 
 ## Model Sources
-For more information regarding this model, please checkout our paper
+For more information regarding this model, please checkout our paper: (TO-DO)
 - **Paper:** https://arxiv.org/pdf/2309.07287.pdf
   
 ## Model Description