Papers by Miaomiao Yu

2 papers
CB-Whisper: Contextual Biasing Whisper Using Open-Vocabulary Keyword-Spotting (2024.lrec-main)

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Challenge: End-to-end automatic speech recognition systems struggle to recognize rare name entities such as personal names, organizations and terminologies that are not frequently encountered in the training data.
Approach: They propose a convolutional neural network-based ASR system that performs open-vocabulary keyword-spotting before the decoder to match the features between the entities and the utterances.
Outcome: The proposed system significantly improves mixed-error-rate (MER) and entity recall compared to the original Whisper model on three internal datasets and two publicly available datasets.
HGCN4MeSH: Hybrid Graph Convolution Network for MeSH Indexing (2020.acl-srw)

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Challenge: Recent deep learning methods for MeSH indexing fail to capture complex correlations between terms.
Approach: They propose a model to learn the relationship between MeSH terms using Graph Convolution Network (GCN) they use two biGRUs to learn embedding representations of abstract and title of MeSH index text .
Outcome: The proposed model is competitive with the state-of-the-art models on two datasets.

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