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---
license: openrail
language:
- en
metrics:
- f1, UAR
library_name: speechbrain
pipeline_tag: audio-classification
---
# Model Card for Model ID
<!-- 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/).
## Model Sources
For more information regarding this model, please checkout our paper
- **Paper:** Coming soon
## Model Description
<!-- Provide a longer summary of what this model is. -->
Folder contains the best checkpoint of the following setting
- **W2V2-MyST by fine-tuning on Librispeech 960h**: save_960h/wav2vec2.ckpt
- **W2V2-Pro trained on phone sequence**: save_MyST_Providence_ep45_filtered/wav2vec2.ckpt
- **W2V2-Pro trained on consonant/vowel sequence**: save_MyST_Providence_ep45_filtered_cv_only/wav2vec2.ckpt
## Uses
**We develop our complete fine-tuning recipe using SpeechBrain toolkit available at**
- **https://github.com/jialuli3/speechbrain/tree/infant-voc-classification/recipes/RABC** (used for Rapid-ABC corpus)
- **https://github.com/jialuli3/speechbrain/tree/infant-voc-classification/recipes/BabbleCor** (used for BabbleCor corpus)
# Paper/BibTex Citation
<!-- If there is a paper or blog post introducing the model, the APA and Bibtex information for that should go in this section. -->
If you found this model helpful to you, please cite us as
Coming soon
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# Model Card Contact
Jialu Li (she, her, hers)
Ph.D candidate @ Department of Electrical and Computer Engineering, University of Illinois at Urbana-Champaign
E-mail: jialuli3@illinois.edu
Homepage: https://sites.google.com/view/jialuli/
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