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Found 9 papers, 3 papers with code
Faces that Speak: Jointly Synthesising Talking Face and Speech from Text
The goal of this work is to simultaneously generate natural talking faces and speech outputs from text.
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.
Active Speaker Detection
Audio-Visual Active Speaker Detection
+1
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.
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.
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.
