Publications by authors named "Colin Vaz"
Article Synopsis
- Real-time magnetic resonance imaging (RT-MRI) is enhancing research in speech science, linguistics, and speech technology, but access to such data is limited.
- Existing raw multi-coil RT-MRI datasets for speech production are lacking, hindering research advancements like dynamic image reconstruction and feature extraction.
- The provided dataset includes 2D RT-MRI videos, synchronized audio from 75 participants, and additional 3D and anatomical MRI scans, making it a valuable resource for advancing speech research.
Acoustic Denoising using Dictionary Learning with Spectral and Temporal Regularization.
IEEE/ACM Trans Audio Speech Lang Process
May 2018
We present a method for speech enhancement of data collected in extremely noisy environments, such as those obtained during magnetic resonance imaging (MRI) scans. We propose an algorithm based on dictionary learning to perform this enhancement. We use complex nonnegative matrix factorization with intra-source additivity (CMF-WISA) to learn dictionaries of the noise and speech+noise portions of the data and use these to factor the noisy spectrum into estimated speech and noise components.
View Article and Find Full Text PDFBarista: A Framework for Concurrent Speech Processing by USC-SAIL.
Proc IEEE Int Conf Acoust Speech Signal Process
May 2014
We present Barista, an open-source framework for concurrent speech processing based on the Kaldi speech recognition toolkit and the libcppa actor library. With Barista, we aim to provide an easy-to-use, extensible framework for constructing highly customizable concurrent (and/or distributed) networks for a variety of speech processing tasks. Each Barista network specifies a flow of data between simple actors, concurrent entities communicating by message passing, modeled after Kaldi tools.
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