Survey on Visual Speech Recognition using Deep Learning Techniques

Ritika Chand, Pushpit Jain, Abhinav Mathur, Shiwansh Raj, Prashasti Kanikar
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引用次数: 1

Abstract

Lip Reading has evolved and from where it began to help deaf people has slowly turned into a service where in the Digital Entertainment industry has started utilizing it. With the recent rise of AI, automated technologies have touched the boundaries of Lip Reading as well. Various Algorithms have been devised using Neural Network Methodologies. We observe that a lot of the algorithms reviewed, have been exploring various techniques whether it be a variation from detecting lip features to the text generation process itself.With the amount of research done in the field, one can always look out towards a better & optimized lip detection. The study emphasizes more towards looking at the utilization of the Machine Learning & Deep Learning technologies and thus provides a vivid view at the bigger picture of the interpolation of AI in the Visual based Lip Reading domain.
基于深度学习技术的视觉语音识别研究综述
唇读已经发展起来,从最初帮助聋哑人开始,慢慢地变成了一种服务,在数字娱乐行业已经开始使用它。随着人工智能的兴起,自动化技术也触及了唇读的界限。使用神经网络方法设计了各种算法。我们观察到,许多被审查的算法一直在探索各种技术,无论是从检测嘴唇特征到文本生成过程本身的变化。随着在该领域所做的大量研究,人们总是可以看到一个更好的和优化的嘴唇检测。该研究更多地强调了机器学习和深度学习技术的应用,从而为基于视觉的唇读领域的人工智能插值提供了一个生动的视角。
本文章由计算机程序翻译,如有差异,请以英文原文为准。
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