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Found 7 papers, 1 papers with code
Leveraging Visemes for Better Visual Speech Representation and Lip Reading
We evaluate our approach on various tasks, including word-level and sentence-level lip reading, and audiovisual speech recognition using the Arman-AV dataset, a largescale Persian corpus.
Word-level Persian Lipreading Dataset
Lip-reading has made impressive progress in recent years, driven by advances in deep learning.
A Multi-Purpose Audio-Visual Corpus for Multi-Modal Persian Speech Recognition: the Arman-AV Dataset
In addition, we have proposed a technique to detect visemes (a visual equivalent of a phoneme) in Persian.
Audio-Visual Speech Recognition
Automatic Speech Recognition
+5
MAS2HP: A Multi Agent System to Predict Protein Structure in 2D HP model
In this paper we proposed a new approach for protein structure prediction by using agent-based modeling (ABM) in two dimensional hydrophobic-hydrophilic model.
Lip reading using external viseme decoding
Lip-reading is the operation of recognizing speech from lip movements.
A new Potential-Based Reward Shaping for Reinforcement Learning Agent
Among the literature of both the transfer learning and the potential-based reward shaping, a subject that has never been addressed is the knowledge gathered during the learning process itself.
Learning to predict where to look in interactive environments using deep recurrent q-learning
Bottom-Up (BU) saliency models do not perform well in complex interactive environments where humans are actively engaged in tasks (e. g., sandwich making and playing the video games).
