5 天之前 · Humans have the ability to utilize visual cues, such as lip movements and visual scenes, to enhance auditory perception, particularly in noisy environments. However, current Automatic Speech Recognition (ASR) or Audio-Visual Speech Recognition (AVSR) models often struggle in noisy scenarios. To solve this task, we propose a model that improves transcription by correlating noise sources to ...

2023年6月1日 · 视觉到语音合成（VTS）旨在根据无声的对话视频（通常为面部或口唇部位），重建出相应的音频信号。 相较于多模态语音识别（Audio-visual Speech Recognition, AVSR）和唇语识别（Lip Reading / Visual Speech Recognition, VSR），VTS任务的研究尚不充分，目前大多数工作仍然在 GRID， TCD-TIMIT 等具有较少说话人和受限词汇量的小规模数据集上进行研究。 但也有一部分工作已经开始涉足多说话人、大词汇量连续语音的数据集，比如LRS2，LRS3。 …

When working with a child who is not able to speak long words, we can begin improving their speech by teaching them to produce sounds in CV, VC, CVC, and CVCV words. These are …

Visual information is often used as a complementary cue for automatic speech recognition in noisy environments. Most previous studies utilize visual information

2025年3月19日 · The recent successes of Vision-Language models raise the question of how to equivalently imbue a pretrained speech model with vision understanding, an important milestone towards building a multimodal speech model able to freely converse about images. Building such a conversational Vision-Speech model brings its unique challenges: (i) paired image-speech datasets are much scarcer than their ...

2025年3月28日 · Humans combine the visual information from mouth movements with auditory information from the voice to recognize speech. A common method for assessing audiovisual speech perception is the McGurk effect: when presented with some incongruent pairings of auditory and visual speech syllables (e.g., the …

分享一篇非常有意思也很有用的文章，是WACV 2021的录用论文Visual Speech Enhancement Without A Real Visual Stream。 该文研究涉及计算机视觉与语音处理的交叉。 论文信息： 作者来自：印度 IIIT Hyderabad 和英…

This paper introduces a new time-domain audio-visual architecture for target speaker extraction from monaural mixtures. The architecture generalizes the previous TasNet (time-domain speech separation network) to enable multi-modal learning and at meanwhile it extends the classical audio-visual speech separation from frequency-domain to time-domain.

2025年2月15日 · By incorporating tools like drill cards, charts, diagrams, and videos, therapists can create a multi-sensory learning experience that supports better understanding and mastery of speech goals. For instance, when teaching correct pronunciation, visuals can serve as a guide for articulatory placement and movement.

2022年9月29日 · Use visuals to enhance speech therapy with students of all ages. From teaching strategies to supplementing practice to sending for home carryover, visuals are invaluable tools for SLPs.