Automatic speech recognition, especially large vocabulary continuous speech recognition,
is an important issue in the field of machine learning. For a long time, the hidden Markov …

Code smells are structures in the source code that suggest the possibility of refactorings.
Consequently, developers may identify refactoring opportunities by detecting code smells …

Recurrent Neural Networks (RNNs) are used for sequence recognition tasks such as
Handwritten Text Recognition (HTR) or speech recognition. If trained with the Connectionist …

Software refactoring is widely employed to improve software quality. A key step in software
refactoring is to identify which part of the software should be refactored. To facilitate the …

In recent years, Handwritten Text Recognition (HTR) has captured a lot of attention among
the researchers of the computer vision community. Current state-of-the-art approaches for …

The increasing portability of physical manuscripts to the digital environment makes it
common for systems to offer automatic mechanisms for offline Handwritten Text Recognition …

In this paper, a neural network based real-time speech recognition (SR) system is
developed using an FPGA for very low-power operation. The implemented system employs …

In Automatic Speech Recognition, it is still challenging to learn useful intermediate
representations when using high-level (or abstract) target units such as words. For that …

We formulate sequence to sequence transduction as a noisy channel decoding problem and
use recurrent neural networks to parameterise the source and channel models. Unlike direct …

Recurrent neural network (RNN) based character-level language models (CLMs) are
extremely useful for modeling out-of-vocabulary words by nature. However, their …