The field of machine translation (MT), the automatic translation of written text from one
natural language into another, has experienced a major paradigm shift in recent years …

Artificial neural networks (ANNs) ability to learn, correct errors, and transform a large amount
of raw data into beneficial medical decisions for treatment and care has increased in …

Language models have traditionally been estimated based on relative frequencies, using
count statistics that can be extracted from huge amounts of text data. More recently, it has …

This work presents two different translation models using recurrent neural networks. The first
one is a word-based approach using word alignments. Second, we present phrase-based …

Like how useful weather forecasting is, the capability of forecasting or predicting cyber
threats can never be overestimated. Previous investigations show that cyber attack data …

This paper presents “BachBot”: an end-to-end automatic composition system for composing
and completing music in the style of Bach's chorales using a deep long short-term memory …

Multi-style training, using data which emulates a variety of possible test scenarios, is a
popular approach towards robust acoustic modeling. However acoustic models capable of …

Recurrent neural network language models (RNNLMs) have recently become increasingly
popular for many applications including speech recognition. In previous research RNNLMs …

In recent years, recurrent neural network language models (RNNLMs) have become
increasingly popular for a range of applications including speech recognition. However, the …

In recent years recurrent neural network language models (RNNLMs) have been
successfully applied to a range of tasks including speech recognition. However, an …