Search Results for author:
Found 8 papers, 2 papers with code
FreGrad: Lightweight and Fast Frequency-aware Diffusion Vocoder
The goal of this paper is to generate realistic audio with a lightweight and fast diffusion-based vocoder, named FreGrad.
Seeing Through the Conversation: Audio-Visual Speech Separation based on Diffusion Model
For an effective fusion of the two modalities for diffusion, we also propose a cross-attention-based feature fusion mechanism.
TalkNCE: Improving Active Speaker Detection with Talk-Aware Contrastive Learning
The goal of this work is Active Speaker Detection (ASD), a task to determine whether a person is speaking or not in a series of video frames.
SlowFast Network for Continuous Sign Language Recognition
The objective of this work is the effective extraction of spatial and dynamic features for Continuous Sign Language Recognition (CSLR).
That's What I Said: Fully-Controllable Talking Face Generation
The goal of this paper is to synthesise talking faces with controllable facial motions.
Self-Sufficient Framework for Continuous Sign Language Recognition
The goal of this work is to develop self-sufficient framework for Continuous Sign Language Recognition (CSLR) that addresses key issues of sign language recognition.
Signing Outside the Studio: Benchmarking Background Robustness for Continuous Sign Language Recognition
Most existing Continuous Sign Language Recognition (CSLR) benchmarks have fixed backgrounds and are filmed in studios with a static monochromatic background.
Metric Learning for User-defined Keyword Spotting
In particular, we make the following contributions: (1) we construct a large-scale keyword dataset with an existing speech corpus and propose a filtering method to remove data that degrade model training; (2) we propose a metric learning-based two-stage training strategy, and demonstrate that the proposed method improves the performance on the user-defined keyword spotting task by enriching their representations; (3) to facilitate the fair comparison in the user-defined KWS field, we propose unified evaluation protocol and metrics.
