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Home » Archives for Horacio Franco
Horacio Franco

Horacio Franco

Chief Scientist, Speech Technology and Research Laboratory
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Publications

Speech & natural language publications July 22, 2020 Conference Paper

Wideband Spectral Monitoring Using Deep Learning

Horacio Franco, Martin Graciarena

We present a system to perform spectral monitoring of a wide band of 666.5 MHz, located within a range of 6 GHz of Radio Frequency (RF) bandwidth, using state-of-the-art deep learning approaches.

Speech & natural language publications June 1, 2018

Voices Obscured in Complex Environmental Settings (VOiCES) corpus

Colleen Richey, Horacio Franco, Aaron Lawson, Allen Stauffer

This work is a multi-organizational effort led by SRI International and Lab41 with the intent to push forward state-of-the-art distant microphone approaches in signal processing and speech recognition.

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 December 1, 2017

Noise-robust Exemplar Matching for Rescoring Query-by-Example Search

Horacio Franco

This paper describes a two-step approach for keyword spotting task in which a query-by-example search is followed by noise robust exemplar matching rescoring. 

Speech & natural language publications August 1, 2017

Leveraging Deep Neural Network Activation Entropy to Cope with Unseen Data in Speech Recognition

Horacio Franco

This work aims to estimate the propagation of such distortion in the form of network activation entropy, which is measured over a short-time running window on the activation from each neuron of a given hidden layer, and these measurements are then used to compute summary entropy. 

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 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 September 1, 2016

Coping with Unseen Data Conditions: Investigating Neural Net Architectures, Robust Features, and Information Fusion for Robust Speech Recognition

Horacio Franco

This work investigates the performance of traditional deep neural networks under varying acoustic conditions and evaluates their performance with speech recorded under realistic background conditions that are mismatched with respect to the training data.

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.

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