This paper deals with Audio-Visual Speech Recognition (AVSR) under multimodal input
corruption situation where audio inputs and visual inputs are both corrupted, which is not …

This paper proposes a novel lip reading framework, especially for low-resource languages,
which has not been well addressed in the previous literature. Since low-resource languages …

Recent research has demonstrated impressive results in video-to-speech synthesis which
involves reconstructing speech solely from visual input. However, previous works have …

In this paper, we propose a novel Lip-to-Speech synthesis (L2S) framework, for synthesizing
intelligible speech from a silent lip movement video. Specifically, to complement the …

This paper proposes a powerful Visual Speech Recognition (VSR) method for multiple
languages, especially for low-resource languages that have a limited number of labeled …

In this paper, we propose methods to build a powerful and efficient Image-to-Speech
captioning (Im2Sp) model. To this end, we start with importing the rich knowledge related to …

The goal of this work is to reconstruct high quality speech from lip motions alone, a task also
known as lip-to-speech. A key challenge of lip-to-speech systems is the one-to-many …

This paper proposes a powerful Visual Speech Recognition (VSR) method for multiple
languages, especially for low-resource languages that have a limited number of labeled …

The integration of visual cues has revitalized the performance of the target speech extraction
task, elevating it to the forefront of the field. Nevertheless, this multi-modal learning paradigm …

In the field of speech synthesis, there is a growing emphasis on employing multimodal
speech to enhance robustness. A key challenge in this area is the scarcity of datasets that …