Lip reading technology refers to the analysis of visual information speaker’s mouth movements recognize content speech. As one important aspects human–computer interaction, lip has gradually become popular with development deep learning in recent years. At present, most networks are very complex, large numbers parameters and computation, model generated by training needs occupy memory, which br...

BACKGROUND Many parents look to various sources for information about parenting when their child has a cleft lip and/or palate. More than 8 million Americans perform health-related searches every day on the World Wide Web. Furthermore, a significant number of them report feeling "overwhelmed" by the language and content of the information. OBJECTIVE The purpose of this study is to determine t...

Results: Key indicators of ALR’s overall progress confirmed ALR’s success across its three goals: (1) establishing a strong research base: 309 publications filling major knowledge gaps; (2) building an interdisciplinary and diverse field: grantees represented 31 disciplines, with more than one quarter (28%) of investigators having r5 years of experience, of which 39% were people of color; and (...

This paper presents a lip localization based visual feature extraction method to segment lip region from image or video in real time. Lip localization and tracking is useful in many applications such as lip reading, lip synchronization, visual speech recognition, facial animation etc. To synchronize lip movements with input audio we need to first segment lip region from input image or video fra...

The goal of this work is to recognize words, phrases, and sentences being spoken by a talking face without given the audio. Current deep learning approaches for lip reading focus on exploring appearance optical flow information videos. However, these methods do not fully exploit characteristics motion. In addition flow, mouth contour deformation usually conveys significant that complementary ot...

Most connectionist research has focused on learning mappings from one space to another (eg. classification and regression). This paper introduces the more general task of learning constraint surfaces. It describes a simple but powerful architecture for learning and manipulating nonlinear surfaces from data. We demonstrate the technique on low dimensional synthetic surfaces and compare it to nea...

This paper describes Japanese phone recognition for lip reading based on a novel feature called trajectory feature to obtain high recognition rate. Trajectory feature is a time change of two mouth shape features expressed as a two-dimensional trajectory of the lip motion. The most similar trajectory in a database which is compared with the target trajectory by DP matching is selected as a resul...