10 accepted papers
With the advancement of large-scale models, the demand for emotionally rich, long-context, and highly natural communication in human-computer interaction increases. However, the exploration of long-context or script-level speech conversation tasks remains limited due to the lack of specific supervis…
The cold-start recommendation has been challenging due to the limited historical interactions for new users and new items. Recently, methods based on meta-learning and graph neural networks have been effective in this problem. However, these methods mainly focus on the missing user-item interactions…
Triton, a high-level Python-like language designed for building efficient GPU kernels, is widely adopted in deep learning frameworks due to its portability, flexibility, and accessibility. However, programming and parallel optimization still require considerable trial and error from Triton developer…
Given one reference facial image and a piece of speech as input, talking head generation aims to synthesize a realistic-looking talking head video. However, generating a lip-synchronized video with natural head movements is challenging. The same speech clip can generate multiple possible lip and hea…
Acoustic-to-articulatory inversion (AAI) aims to estimate the parameters of articulators from speech audio. There are two common challenges in AAI, which are the limited data and the unsatisfactory performance in speaker independent scenario. Most current works focus on extracting features directly…
Acoustic-to-articulatory inversion (AAI) is to obtain the movement of articulators from speech signals. Until now, achieving a speaker-independent AAI remains a challenge given the limited data. Besides, most current works only use audio speech as input, causing an inevitable performance bottleneck.…
Previous works derive personalized speech features by training the model on a large dataset composed of his/her audio sounds. It was reported that face information has a strong link with the speech sound. Thus in this work, we innovatively extract personalized speech features from human faces to syn…
In self-supervised monocular depth estimation, the depth discontinuity and motion objects' artifacts are still challenging problems. Existing self-supervised methods usually utilize two views to train the depth estimation network and use one single view to make predictions. Compared with static view…
This study describes a nonlinear geometric tongue model based on MRI and Cone-beam CT (CBCT) data. Comparing with the conventional geometric tongue model, the proposed tongue model is controlled by several prototype vertices, and the relationship between tongue mesh vertices and prototype vertices a…
The movement of tongue plays an important role in pronunciation. Visualizing the movement of tongue can improve speech intelligibility and also helps learning a second language. However, hardly any research has been investigated for this topic. In this paper, a framework to synthesize continuous ult…