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Strategies for High Accuracy Keyword Detection in Noisy Channels

by Arindam M, Julien Van Hout, Yik-cheung Tam, Vikramjit Mitra, Yun Lei, Jing Zheng, Dimitra Vergyri, Luciana Ferrer, Martin Graciarena, Andreas Kathol, Horacio Franco
"... We present design strategies for a keyword spotting (KWS) sys-tem that operates in highly degraded channel conditions with very low signal-to-noise ratio levels. We employ a system combination approach by combining the outputs of multiple large vocabulary automatic speech recognition (LVCSR) sys-tem ..."
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We present design strategies for a keyword spotting (KWS) sys-tem that operates in highly degraded channel conditions with very low signal-to-noise ratio levels. We employ a system combination approach by combining the outputs of multiple large vocabulary automatic speech recognition (LVCSR) sys

Strategies for High Accuracy Keyword Detection in Noisy Channels

by Arindam Mandal , Julien Van Hout , Yik-Cheung Tam , Vikramjit Mitra , Yun Lei , Jing Zheng , Dimitra Vergyri , Luciana Ferrer , Martin Graciarena , Andreas Kathol , Horacio Franco
"... Abstract We present design strategies for a keyword spotting (KWS) system that operates in highly degraded channel conditions with very low signal-to-noise ratio levels. We employ a system combination approach by combining the outputs of multiple large vocabulary automatic speech recognition (LVCSR ..."
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Abstract We present design strategies for a keyword spotting (KWS) system that operates in highly degraded channel conditions with very low signal-to-noise ratio levels. We employ a system combination approach by combining the outputs of multiple large vocabulary automatic speech recognition

C-means Clustering applied to Speech Discrimination

by J. M. Górriz, J. Ramírez, I. Turias, C. G. Puntonet, J. González, E. W. Lang, Ag Neuro- Und Bioinformatik, Universität Regensburg
"... Abstract. An effective voice activity detection (VAD) algorithm is proposed for improving speech recognition performance in noisy environments. The proposed speech/pause discrimination method is based on a hard-decision clustering approach built over a set of subband logenergies. Detecting the prese ..."
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Abstract. An effective voice activity detection (VAD) algorithm is proposed for improving speech recognition performance in noisy environments. The proposed speech/pause discrimination method is based on a hard-decision clustering approach built over a set of subband logenergies. Detecting

Active Mask Framework for Segmentation of Fluorescence Microscope Images

by Gowri Srinivasa, Advisor Prof, Prof Matthew, C. Fickus, Prof Adam, D. Linstedt, Prof Robert, F. Murphy
"... m]]l]]s¶D]]¿÷mB]iv]b]oD]m¶¨]iv]§]iv]r]j]t¿rv]]irj]]t]]m] / | ap]]r¿]ÎNy]s¶D]]mb¶r]ix} Û]Ix]]rd]mb]} p—N]t]o%ism] in]ty]m] / || Û]Is]¡uÎc]rN]]riv]nd]p]*N]m]st¶ I always bow to Śri ̄ Śāradāmbā, the limitless ocean of the nectar of compassion, who bears a rosary, a vessel of nectar, the symbol of ..."
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facilitated the task of understanding complex sys-tems at cellular and molecular levels in recent years. Segmentation, an important yet dif-ficult problem, is often the first processing step following acquisition. Our team previously demonstrated that a stochastic active contour based algorithm together

RICE UNIVERSITY Regime Change: Sampling Rate vs. Bit-Depth in Compressive Sensing

by Jason Noah Laska , 2011
"... The compressive sensing (CS) framework aims to ease the burden on analog-to-digital converters (ADCs) by exploiting inherent structure in natural and man-made signals. It has been demon-strated that structured signals can be acquired with just a small number of linear measurements, on the order of t ..."
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accommodate the otherwise limiting quantizer of conventional ADCs. In this thesis, we consider a different approach to CS ADC by shifting towards lower quantizer bit-depths rather than lower sampling rates. We explore the extreme case where each measurement is quantized to just one bit, representing its sign

port Vector Machines, Kernel Fisher Discriminant analysis

by Sebastian Mika, Koji Tsuda
"... Abstract | This review provides an introduction to Sup- ..."
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Abstract | This review provides an introduction to Sup-

under a Creative Commons Attribution Non-Commercial No Derivatives

by Sira Gonzalez, Deparment Of Electrical, Electronic Engineering , 2013
"... the condition that they attribute it, that they do not use it for commercial purposes and that they do not alter, transform or build upon it. For any reuse or redistribution, researchers must make clear to others the licence terms of this work. ..."
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the condition that they attribute it, that they do not use it for commercial purposes and that they do not alter, transform or build upon it. For any reuse or redistribution, researchers must make clear to others the licence terms of this work.

1C-HiLasso: A Collaborative Hierarchical Sparse Modeling Framework

by Pablo Sprechmann, Guillermo Sapiro, Yonina C. Eldar
"... Sparse modeling is a powerful framework for data analysis and processing. Traditionally, encoding in this framework is performed by solving an `1-regularized linear regression problem, commonly referred to as Lasso or Basis Pursuit. In this work we combine the sparsity-inducing property of the Lasso ..."
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then extend this approach to the collaborative case, where a set of simultaneously coded signals share the same sparsity pattern at the higher (group) level, but not necessarily at the lower (inside the group) level, obtaining the collaborative HiLasso model (C-HiLasso). Such signals then share the same
Results 1 - 8 of 8