Compared to feature or decision fusion, hybrid fusion can beneficially improve audio-visual
speech recognition accuracy. Existing works are mainly prone to design the multi-modality …

Compared to relying only on audio information, incorporating visual information improves
speech recognition accuracy in noisy environments. Existing works are prone to design …

Automatic speech recognition (ASR) is the major human–machine interface in many
intelligent systems, such as intelligent homes, autonomous driving, and servant robots …

In recent years, multimodal fusion using deep learning has proliferated in various tasks such
as emotion recognition, and speech recognition by drastically enhancing the performance of …

In recent research, slight performance improvement is observed from automatic speech
recognition systems to audio-visual speech recognition systems in end-to-end frameworks …

While automatic speech recognition (ASR) systems degrade significantly in noisy
environments, audio-visual speech recognition (AVSR) systems aim to complement the …

The fusion of audio and visual modalities is an important stage of audio-visual speech
recognition (AVSR), which is generally approached through feature fusion or decision …

Automatic speech recognition (ASR) is a typical pattern recognition technology that converts
human speeches into texts. With the aid of advanced deep learning models, the …

Audio-visual speech recognition (AVSR) integrates both audio and visual information to
perform automatic speech recognition (ASR), which improves the robustness of human …

Audio-visual speech recognition (AVSR) system is thought to be one of the most promising
solutions for robust speech recognition, especially in noisy environment. In this paper, we …