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Submodular subset selection for large-scale speech training data
We address the problem of subselecting a large set of acoustic data to train automatic speech recognition (ASR) systems. To this end, we apply a novel data selection technique based on constrainedExpand
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Deep Contextualized Acoustic Representations for Semi-Supervised Speech Recognition
We propose a novel approach to semi-supervised automatic speech recognition (ASR). We first exploit a large amount of unlabeled audio data via representation learning, where we reconstruct a temporalExpand
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Graph-based semi-supervised learning for phone and segment classification
This paper presents several novel contributions to the emerging framework of graph-based semi-supervised learning for speech processing. First, we apply graphbased learning to variable-lengthExpand
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Using Document Summarization Techniques for Speech Data Subset Selection
In this paper we leverage methods from submodular function optimization developed for document summarization and apply them to the problem of subselecting acoustic data. We evaluate our results onExpand
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Submodular feature selection for high-dimensional acoustic score spaces
We apply methods for selecting subsets of dimensions from high-dimensional score spaces, and subsets of data for training, using submodular function optimization. Submodular functions provideExpand
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Scenario Reduction With Submodular Optimization
Stochastic programming methods have been proven to deal effectively with the uncertainty and variability of renewable generation resources. However, the quality of the solution that they provide (asExpand
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Unsupervised submodular subset selection for speech data
We conduct a comparative study on selecting subsets of acoustic data for training phone recognizers. The data selection problem is approached as a constrained submodular optimization problem.Expand
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Decoding Ipsilateral Finger Movements from ECoG Signals in Humans
Several motor related Brain Computer Interfaces (BCIs) have been developed over the years that use activity decoded from the contralateral hemisphere to operate devices. Contralateral primary motorExpand
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Graph-Based Semisupervised Learning for Acoustic Modeling in Automatic Speech Recognition
  • Y. Liu, K. Kirchhoff
  • Computer Science
  • IEEE/ACM Transactions on Audio, Speech, and…
  • 1 November 2016
In this paper, we investigate how to apply graph-based semisupervised learning to acoustic modeling in speech recognition. Graph-based semisupervised learning is a widely used transductiveExpand
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SVitchboard-II and FiSVer-I: Crafting high quality and low complexity conversational english speech corpora using submodular function optimization
Abstract We introduce a set of benchmark corpora of conversational English speech derived from the Switchboard-I and Fisher datasets. Traditional automatic speech recognition (ASR) research requiresExpand
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