Arabic Machine Transliteration using an Attention-based Encoder-decoder Model

Video Summarization with Attention-Based Encoder-Decoder Networks

This paper addresses the problem of supervised video summarization by formulating it as a sequence-to-sequence learning problem, where the input is a sequence of original video frames, the output is a keyshot sequence. Our key idea is to learn a deep summarization network with attention mechanism to mimic the way of selecting the keyshots of human. To this end, we propose a novel video summariz...

Sangam: A Perso-Arabic to Indic Script Machine Transliteration Model

Indian sub-continent is one of those unique parts of the world where single languages are written in different scripts. This is the case for example with Punjabi, written in Indian East Punjab in Gurmukhi script (a Left to Right script based on Devnagri) and in Pakistani West Punjab, it is written in Shahmukhi (a Right to Left script based on Perso-Arabic). This is also the case with other lang...

Machine Transliteration of Names in Arabic Texts

Implicit Distortion and Fertility Models for Attention-based Encoder-Decoder NMT Model

Neural machine translation has shown very promising results lately. Most NMT models follow the encoder-decoder framework. To make encoder-decoder models more flexible, attention mechanism was introduced to machine translation and also other tasks like speech recognition and image captioning. We observe that the quality of translation by attention-based encoder-decoder can be significantly damag...

Attention-based Information Fusion using Multi-Encoder-Decoder Recurrent Neural Networks

With the rising number of interconnected devices and sensors, modeling distributed sensor networks is of increasing interest. Recurrent neural networks (RNN) are considered particularly well suited for modeling sensory and streaming data. When predicting future behavior, incorporating information from neighboring sensor stations is often beneficial. We propose a new RNN based architecture for c...