7 citations · 14 across the 5 of their papers we have counts for
5 papers
Leveraging Visemes for Better Visual Speech Representation and Lip Reading
Javad Peymanfard, Vahid Saeedi, Mohammad Reza Mohammadi +2
Lip reading is a challenging task that has many potential applications in speech recognition, human-computer interaction, and security systems. However, existing lip reading system…
Word-level Persian Lipreading Dataset
Javad Peymanfard, Ali Lashini, Samin Heydarian +2
Lip-reading has made impressive progress in recent years, driven by advances in deep learning. Nonetheless, the prerequisite such advances is a suitable dataset. This paper provide…
ArmanTTS single-speaker Persian dataset
Mohammd Hasan Shamgholi, Vahid Saeedi, Javad Peymanfard +2
TTS, or text-to-speech, is a complicated process that can be accomplished through appropriate modeling using deep learning methods. In order to implement deep learning models, a su…
A Multi-Purpose Audio-Visual Corpus for Multi-Modal Persian Speech Recognition: the Arman-AV Dataset
Javad Peymanfard, Samin Heydarian, Ali Lashini +3
In recent years, significant progress has been made in automatic lip reading. But these methods require large-scale datasets that do not exist for many low-resource languages. In t…
ArmanEmo: A Persian Dataset for Text-based Emotion Detection
Hossein Mirzaee, Javad Peymanfard, Hamid Habibzadeh Moshtaghin +1
With the recent proliferation of open textual data on social media platforms, Emotion Detection (ED) from Text has received more attention over the past years. It has many applicat…