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Home » Archives for Dimitra Vergyri
Dimitra Vergyri

Dimitra Vergyri

Director, Speech Technology and Research Laboratory (STAR)
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Publications

Information & computer science publications April 17, 2020

Speech‐based markers for post traumatic stress disorder in US veterans

Andreas Tsiartas, Colleen Richey, Jennifer Smith, Bruce Knoth, Dimitra Vergyri

This study demonstrates that a speech-based algorithm can objectively differentiate PTSD cases from controls.

Speech & natural language publications December 1, 2017

Tackling Unseen Acoustic Conditions in Query-by-Example Search Using Time and Frequency Convolution for Multilingual Deep Bottleneck Features

Horacio Franco, Dimitra Vergyri

This paper revisits two neural network architectures developed for noise  and  channel-robust  ASR,  and  applies  them  to  building a  state-of-art  multilingual  QbE  system.

Speech & natural language publications March 1, 2017

Speech recognition in unseen and noisy channel conditions

Horacio Franco, Martin Graciarena, Dimitra Vergyri

This work investigates robust features, feature-space maximum likelihood linear regression (fMLLR) transform, and deep convolutional nets to address the problem of unseen channel and noise conditions in speech recognition.

Speech & natural language publications March 1, 2017

Toward human-assisted lexical unit discovery without text resources

Andreas Kathol, Dimitra Vergyri, Harry Bratt

This work addresses lexical unit discovery for languages without (usable) written resources.

Speech & natural language publications March 1, 2017

Joint modeling of articulatory and acoustic spaces for continuous speech recognition tasks

Dimitra Vergyri, Horacio Franco

This  paper  investigates using deep neural networks (DNN) and convolutional neural networks (CNNs) for mapping speech data into its corresponding articulatory space. 

Speech & natural language publications September 1, 2016 Conference Paper

Fusion Strategies for Robust Speech Recognition and Keyword Spotting for Channel- and Noise-Degraded Speech

Dimitra Vergyri

Current state-of-the-art automatic speech recognition systems are sensitive to changing acoustic conditions, which can cause significant performance degradation.

Speech & natural language publications September 1, 2016

Unsupervised Learning of Acoustic Units Using Autoencoders and Kohonen Nets

Dimitra Vergyri, Horacio Franco

This work investigates learning acoustic units in an unsupervised manner from real-world speech data by using a cascade of an autoencoder and a Kohonen net.

Speech & natural language publications December 1, 2015 Conference Paper

Improving robustness against reverberation for automatic speech recognition

Mitchell McLaren, Martin Graciarena, Horacio Franco, Dimitra Vergyri

In this work, we explore the role of robust acoustic features motivated by human speech perception studies, for building ASR systems robust to reverberation effects.

Speech & natural language publications September 1, 2015 Conference Paper

Speech-based assessment of PTSD in a military population using diverse feature classes

Bruce Knoth, Dimitra Vergyri, Mitchell McLaren

We analyzed recordings of the Clinician-Administered PTSD Scale (CAPS) interview from military personnel diagnosed as PTSD positive versus negative.

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