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1
Making Semantic Information Work Effectively for Degraded Environments
In: DTIC (2013)
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2
Accelerating Exploitation of Low-grade Intelligence through Semantic Text Processing of Social Media
In: DTIC (2013)
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3
QUT Para at TREC 2012 Web Track: Word Associations for Retrieving Web Documents
In: DTIC (2012)
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4
Speaker Clustering for a Mixture of Singing and Reading (Preprint)
In: DTIC (2012)
Abstract: In this study, we propose a speaker clustering algorithm based on reading and singing speech samples for each speaker. As a speaking style, singing introduces changes in the time-frequency structure of a speaker s voice. The purpose of this study is to introduce advancements into speech systems such as speech indexing and retrieval which improve robustness to intrinsic variations in speech production. Clustering is performed within a GMM mean supervector space. The proposed method includes two stages: first, initial clusters are obtained using traditional clustering techniques such as k-means, and hierarchical. Next, each cluster is refined in a PLDA subspace resulting in a more speaker dependent representation that is less sensitive to speaking style. The proposed algorithm improves the average clustering accuracy of the k-means baseline by +9.3% absolute. ; The original document contains color images. This paper was accepted for publication in the Proceedings of Interspeech, Portland, Oregon, 9-13 Sept-2012.
Keyword: *INFORMATION RETRIEVAL; *SPEECH RECOGNITION; ALGORITHMS; BASE LINES; CLUSTERING; FREQUENCY; INDEXES; MEAN; MIXTURES; NOISE(SOUND); PE35885G; READING; SAMPLING; SPEAKER CLUSTERING; SPEAKER INDEXING; SPEECH; SPEECH PRODUCTION; SYMPOSIA; Theoretical Mathematics; Voice Communications; WUAFRL3188BAAE
URL: http://www.dtic.mil/docs/citations/ADA568317
http://oai.dtic.mil/oai/oai?&verb=getRecord&metadataPrefix=html&identifier=ADA568317
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5
SAWUS: Siena's Automatic Wikipedia Update System
In: DTIC (2012)
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6
Entity List Completion Using Set Expansion Techniques
In: DTIC (2011)
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7
Related Entity Finding: University of Waterloo at TREC 2010 Entity Track
In: DTIC (2010)
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8
RMIT University at TREC 2009: Web Track
In: DTIC (2009)
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9
A Novel Framework for Related Entities Finding: ICTNET at TREC 2009 Entity Track
In: DTIC (2009)
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10
Relevance Feedback based on Constrained Clustering: FDU at TREC 09
In: DTIC (2009)
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11
A Journey in Entity Related Retrieval for TREC 2009
In: DTIC (2009)
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12
ICTNET at Web Track 2009 Diversity task
In: DTIC (2009)
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13
Lucene for n-grams using the ClueWeb Collection
In: DTIC (2009)
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14
BIT at TREC 2009 Faceted Blog Distillation Task
In: DTIC (2009)
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15
Sparse Matrix Factorization: Applications to Latent Semantic Indexing
In: DTIC (2009)
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16
IRRA at TREC 2009: Index Term Weighting based on Divergence From Independence Model
In: DTIC (2009)
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17
Delft University at the TREC 2009 Entity Track: Ranking Wikipedia Entities
In: DTIC (2009)
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18
POSTECH at TREC 2009 Blog Track: Top Stories Identification
In: DTIC (2009)
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19
Entity Retrieval by Hierarchical Relevance Model, Exploiting the Structure of Tables and Learning Homepage Classifiers
In: DTIC (2009)
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20
University of Padua at TREC 2009: Relevance Feedback Track
In: DTIC (2009)
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