Attention-based encoder-decoder architectures such as Listen, Attend, and Spell (LAS),
subsume the acoustic, pronunciation and language model components of a traditional …

Assistive speech-based technologies can improve the quality of life for people affected with
dysarthria, a motor speech disorder. In this paper, we explore multiple ways to improve …

Dysarthric speech recognition is a highly challenging task. The articulatory motor control
problems associated with neuromotor conditions produce large mismatch against normal …

In this paper we look at recent advances in artificial intelligence. Decades in the making, a
confluence of several factors in the past few years has culminated in a string of …

In this paper, continuous Punjabi speech recognition model is presented using Kaldi toolkit.
For speech recognition, the extraction of Mel frequency cepstral coefficients (MFCC) features …

With increasing global demand for learning English as a second language, there has been
considerable interest in methods of automatic assessment of spoken language proficiency …

This thesis, first defines the goal of Keyword Spotting from a Decision Theory perspective.
Then, the problem is tackled following a probabilistic formulation. More precisely, Keyword …

Recurrent neural networks (NN) with long short-term memory (LSTM) are the current state of
the art to model long term dependencies. However, recent studies indicate that NN …

In this paper we develop a Turkish speech recognition (SR) system using deep neural
networks and compare it with the previous state-of-the-art traditional Gaussian mixture …

This work proposes to incorporate paired phone-posteriors as input features into a neural
net (NN) model for assessing ESL learner's pronunciation quality. In this work, posteriors of …