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 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 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 and BabbleCor.
Model Sources
For more information regarding this model, please checkout our paper
- Paper: https://arxiv.org/pdf/2309.07287.pdf
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 <pre><code> @article{li2023enhancing, title={Enhancing Child Vocalization Classification in Multi-Channel Child-Adult Conversations Through Wav2vec2 Children ASR Features}, author={Li, Jialu and Hasegawa-Johnson, Mark and Karahalios, Karrie}, journal={arXiv preprint arXiv:2309.07287}, year={2023} } </code></pre>
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/
