Papers by Zhaoci Liu

2 papers
Text Classification by Contrastive Learning and Cross-lingual Data Augmentation for Alzheimer’s Disease Detection (2020.coling-main)

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Challenge: Existing methods for AD detection are too expensive and time-consuming to cover all potential patients.
Approach: They propose a contrastive learning method to obtain effective text representations based on monolingual embeddings of BERT and a cross-lingual data augmentation method by building autoencoders to learn the text representation shared by both languages.
Outcome: The proposed method outperforms other methods on a Mandarin AD corpus and achieves 81.6% detection accuracy.
DiffStyleTTS: Diffusion-based Hierarchical Prosody Modeling for Text-to-Speech with Diverse and Controllable Styles (2025.coling-main)

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Challenge: Existing models for text-to-speech (TTS) synthesize speech with acoustic features . autoregressive models have problems with word skipping and repeated reading . non-autoregressive acustic models lack probabilistic modeling and unimodal characteristics of Gaussian distribution don't conform to true distribution of aural features, which restricts the diversity of generated prosodic features.
Approach: They propose a multi-speaker acoustic model that hierarchically models speech prosodic features and controls different prosodic styles to guide prosody prediction.
Outcome: The proposed method outperforms baseline models in naturalness and achieves superior synthesis speed compared to baseline models.

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