A Comprehensive Survey of Advancement in Lip Reading Models: Techniques and Future Directions

IF 2.2 4区 计算机科学 Q3 COMPUTER SCIENCE, ARTIFICIAL INTELLIGENCE
Sampada Deshpande, Kalyani Shirsath, Amey Pashte, Pratham Loya, Sandip Shingade, Vijay Sambhe
{"title":"A Comprehensive Survey of Advancement in Lip Reading Models: Techniques and Future Directions","authors":"Sampada Deshpande,&nbsp;Kalyani Shirsath,&nbsp;Amey Pashte,&nbsp;Pratham Loya,&nbsp;Sandip Shingade,&nbsp;Vijay Sambhe","doi":"10.1049/ipr2.70095","DOIUrl":null,"url":null,"abstract":"<p>Lip reading models improve information processing and decision-making by quickly and accurately comprehending enormous amounts of text. This study dives into the important role that lip reading plays in making communication more inclusive, especially for individuals with hearing impairments. From 2020 to 2024, the researchers carefully examine the progress made in lip-reading algorithms. They take a close look at the methods, innovations and principles used to decode spoken content from videos, specifically using visual speech recognition techniques. The study also emphasises the use of datasets like LRW, LRS2 and LRS3, which are crucial for this exploration. This paper offers valuable insights into recent advancements and highlights the importance of diverse datasets in improving lip-reading models. Its findings aim to guide future research efforts in making communication more accessible for people with hearing impairments.</p>","PeriodicalId":56303,"journal":{"name":"IET Image Processing","volume":"19 1","pages":""},"PeriodicalIF":2.2000,"publicationDate":"2025-07-14","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"https://onlinelibrary.wiley.com/doi/epdf/10.1049/ipr2.70095","citationCount":"0","resultStr":null,"platform":"Semanticscholar","paperid":null,"PeriodicalName":"IET Image Processing","FirstCategoryId":"94","ListUrlMain":"https://ietresearch.onlinelibrary.wiley.com/doi/10.1049/ipr2.70095","RegionNum":4,"RegionCategory":"计算机科学","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":null,"EPubDate":"","PubModel":"","JCR":"Q3","JCRName":"COMPUTER SCIENCE, ARTIFICIAL INTELLIGENCE","Score":null,"Total":0}
引用次数: 0

Abstract

Lip reading models improve information processing and decision-making by quickly and accurately comprehending enormous amounts of text. This study dives into the important role that lip reading plays in making communication more inclusive, especially for individuals with hearing impairments. From 2020 to 2024, the researchers carefully examine the progress made in lip-reading algorithms. They take a close look at the methods, innovations and principles used to decode spoken content from videos, specifically using visual speech recognition techniques. The study also emphasises the use of datasets like LRW, LRS2 and LRS3, which are crucial for this exploration. This paper offers valuable insights into recent advancements and highlights the importance of diverse datasets in improving lip-reading models. Its findings aim to guide future research efforts in making communication more accessible for people with hearing impairments.

Abstract Image

Abstract Image

Abstract Image

Abstract Image

唇读模型研究进展综述:技术与未来发展方向
唇读模型通过快速准确地理解大量文本来提高信息处理和决策能力。这项研究深入探讨了唇读在使交流更具包容性方面所起的重要作用,尤其是对有听力障碍的人来说。从2020年到2024年,研究人员仔细研究了唇读算法的进展。他们仔细研究了从视频中解码语音内容的方法、创新和原理,特别是使用视觉语音识别技术。该研究还强调了LRW、LRS2和LRS3等数据集的使用,这些数据集对这一探索至关重要。本文对最近的进展提供了有价值的见解,并强调了不同数据集在改进唇读模型中的重要性。其研究结果旨在指导未来的研究工作,使听力受损的人更容易沟通。
本文章由计算机程序翻译,如有差异,请以英文原文为准。
求助全文
约1分钟内获得全文 求助全文
来源期刊
IET Image Processing
IET Image Processing 工程技术-工程:电子与电气
CiteScore
5.40
自引率
8.70%
发文量
282
审稿时长
6 months
期刊介绍: The IET Image Processing journal encompasses research areas related to the generation, processing and communication of visual information. The focus of the journal is the coverage of the latest research results in image and video processing, including image generation and display, enhancement and restoration, segmentation, colour and texture analysis, coding and communication, implementations and architectures as well as innovative applications. Principal topics include: Generation and Display - Imaging sensors and acquisition systems, illumination, sampling and scanning, quantization, colour reproduction, image rendering, display and printing systems, evaluation of image quality. Processing and Analysis - Image enhancement, restoration, segmentation, registration, multispectral, colour and texture processing, multiresolution processing and wavelets, morphological operations, stereoscopic and 3-D processing, motion detection and estimation, video and image sequence processing. Implementations and Architectures - Image and video processing hardware and software, design and construction, architectures and software, neural, adaptive, and fuzzy processing. Coding and Transmission - Image and video compression and coding, compression standards, noise modelling, visual information networks, streamed video. Retrieval and Multimedia - Storage of images and video, database design, image retrieval, video annotation and editing, mixed media incorporating visual information, multimedia systems and applications, image and video watermarking, steganography. Applications - Innovative application of image and video processing technologies to any field, including life sciences, earth sciences, astronomy, document processing and security. Current Special Issue Call for Papers: Evolutionary Computation for Image Processing - https://digital-library.theiet.org/files/IET_IPR_CFP_EC.pdf AI-Powered 3D Vision - https://digital-library.theiet.org/files/IET_IPR_CFP_AIPV.pdf Multidisciplinary advancement of Imaging Technologies: From Medical Diagnostics and Genomics to Cognitive Machine Vision, and Artificial Intelligence - https://digital-library.theiet.org/files/IET_IPR_CFP_IST.pdf Deep Learning for 3D Reconstruction - https://digital-library.theiet.org/files/IET_IPR_CFP_DLR.pdf
×
引用
GB/T 7714-2015
复制
MLA
复制
APA
复制
导出至
BibTeX EndNote RefMan NoteFirst NoteExpress
×
提示
您的信息不完整,为了账户安全,请先补充。
现在去补充
×
提示
您因"违规操作"
具体请查看互助需知
我知道了
×
提示
确定
请完成安全验证×
copy
已复制链接
快去分享给好友吧!
我知道了
右上角分享
点击右上角分享
0
联系我们:info@booksci.cn Book学术提供免费学术资源搜索服务,方便国内外学者检索中英文文献。致力于提供最便捷和优质的服务体验。 Copyright © 2023 布克学术 All rights reserved.
京ICP备2023020795号-1
ghs 京公网安备 11010802042870号
Book学术文献互助
Book学术文献互助群
群 号:604180095
Book学术官方微信