Lip Reading Sentences Using Deep Learning With Only Visual Cues
نویسندگان
چکیده
منابع مشابه
Deep Learning for Lip Reading using Audio-Visual Information for Urdu Language
Human lip-reading is a challenging task. It requires not only knowledge of underlying language but also visual clues to predict spoken words. Experts need certain level of experience and understanding of visual expressions learning to decode spoken words. Now-a-days, with the help of deep learning it is possible to translate lip sequences into meaningful words. The speech recognition in the noi...
متن کاملLearning Visual Models for Lip Reading
This chapter describes learning techniques that are the basis of a "visual speech recognition" or "lipreading" system 1 • Model-based vision systems currently have the best performance for many visual recognition tasks. For geometrically simple domains, models can sometimes be constructed by hand using CAD-like tools. Such models are difficult and expensive to construct, however, and are inadeq...
متن کاملShallow Reading with Deep Learning: Predicting Popularity of Online Content Using only Its Title
With the ever decreasing attention span of contemporary Internet users, the title of online content (such as a news article or video) can be a major factor in determining its popularity. To take advantage of this phenomenon, we propose a new method based on a bidirectional Long Short-Term Memory (LSTM) neural network designed to predict the popularity of online content using only its title. We ...
متن کاملReading Comprehension with Deep Learning
We train a model that combines attention with multi-perspective matching to perform question answering. For each question and context pair in SQuAD, we perform an attention calculation over each context before extracting features of the question and context, matching them from multiple perspectives. Whilst we did not have time to perform a hyper-parameter search or incorporate other features in...
متن کاملImproving visual features for lip-reading
Automatic speech recognition systems that utilise the visual modality of speech often are investigated within a speakerdependent or a multi-speaker paradigm. That is, during training the recogniser will have had prior exposure to example speech from each of the possible test speakers. In a previous paper we highlighted the danger of not using different speakers in the training and test sets, an...
متن کاملذخیره در منابع من
با ذخیره ی این منبع در منابع من، دسترسی به آن را برای استفاده های بعدی آسان تر کنید
ژورنال
عنوان ژورنال: IEEE Access
سال: 2020
ISSN: 2169-3536
DOI: 10.1109/access.2020.3040906