Publications
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Combining Feature Sets with Support Vector Machines: Application to Speaker Recognition
In this paper, we describe a general technique for optimizing the relative weights of feature sets in a support vector machine (SVM) and show how it can be applied to…
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Four Weightings and a Fusion: A Cepstral-SVM System for Speaker Recognition
A new speaker recognition system is described that uses Mel-frequency cepstral features. This system is a combination of four support vector machines (SVMs). All the SVM systems use polynomial features…
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Multirate ASR Models for Phone-Class Dependent N-Best List Rescoring
In this work, we describe a technique to augment a recognizer that uses this compromise with information from multiple-rate spectral models that emphasize either better time or better frequency resolution…
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VERL: An ontology framework for representing and annotating video events
This article describes the findings of a recent workshop series that has produced an ontology framework for representing video events-called Video Event Representation Language (VERL) -and a companion annotation framework,…
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Task Management under Change and Uncertainty: Constraint Solving Experience with the CALO Project
We outline the challenges and opportunities presented by constraint solving in the presence of change and uncertainty, embodied in CALO's personalized time management and task reasoning and execution systems.
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Singapore Tablet PC Program Study: Executive Summary and Final Report, Volume 1, Technical Findings
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Mapping The Distribution Of Expertise And Resources In A School: Investigating The Potential Of Using Social Network Analysis In Evaluation
This paper describes results of a study investigating the potential of using social network analysis to evaluate the capacity of a school to undertake a schoolwide educational reform.
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Singapore Tablet PC Program Study: Executive Summary and Final Report, Volume 2, Technical Appendicies
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Comparing HMM, Maximum Entropy, and Conditional Random Fields for Disfluency Detection
We compare a generative hidden Markov model (HMM)-based approach and two conditional models — a maximum entropy (Maxent) model and a conditional random field (CRF) — for detecting disfluencies in…
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Distinguishing Deceptive from Non-Deceptive Speech
We present results from a study seeking to distinguish deceptive from non-deceptive speech using machine learning techniques on features extracted from a large corpus of deceptive and non-deceptive speech. We…
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Improved Discriminative Training Using Phone Lattices
We present an efficient discriminative training procedure utilizing phone lattices. Different approaches to expediting lattice generation, statistics collection, and convergence were studied.
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Generation of fast interpreters for Huffman compressed bytecode
Our approach uses canonical Huffman codes to generate compact opcodes with custom-sized operand fields and with a virtual machine that directly executes this compact code. In effect, this automatically creates…