Papers by Daijiao Liu
When LLMs Meets Acoustic Landmarks: An Efficient Approach to Integrate Speech into Large Language Models for Depression Detection (2024.emnlp-main)
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| Challenge: | Large language models (LLMs) are used for depression detection but their application remains unexplored. |
| Approach: | They propose to integrate acoustic speech information into LLMs for depression detection by integrating aural landmarks into the framework. |
| Outcome: | The proposed method adds critical dimensions to speech transcripts and provides insights into the unique speech patterns of individuals. |
Speaking in Wavelet Domain: A Simple and Efficient Approach to Speed up Speech Diffusion Model (2024.emnlp-main)
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Xiangyu Zhang, Daijiao Liu, Hexin Liu, Qiquan Zhang, Hanyu Meng, Leibny Paola Garcia Perera, EngSiong Chng, Lina Yao
| Challenge: | Existing approaches to enhance inference speed and training require complex modifications to the model. |
| Approach: | They propose to double the training and inference speed of Denoising Diffusion Probabilistic Models by simply redirecting the generative target to the wavelet domain. |
| Outcome: | The proposed method doubles the training and inference speed of Speech DDPMs by redirecting the generative target to the wavelet domain. |