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» Learning with Annotation Noise
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ICASSP
2011
IEEE
14 years 1 months ago
A non-negative approach to semi-supervised separation of speech from noise with the use of temporal dynamics
We present a semi-supervised source separation methodology to denoise speech by modeling speech as one source and noise as the other source. We model speech using the recently pro...
Gautham J. Mysore, Paris Smaragdis
68
Voted
LREC
2010
149views Education» more  LREC 2010»
14 years 11 months ago
Paragraph Acquisition and Selection for List Question Using Amazon's Mechanical Turk
Creating more fine-grained annotated data than previously relevent document sets is important for evaluating individual components in automatic question answering systems. In this...
Fang Xu, Dietrich Klakow
63
Voted
COLT
2006
Springer
15 years 1 months ago
Optimal Oracle Inequality for Aggregation of Classifiers Under Low Noise Condition
We consider the problem of optimality, in a minimax sense, and adaptivity to the margin and to regularity in binary classification. We prove an oracle inequality, under the margin ...
Guillaume Lecué
100
Voted
MIR
2006
ACM
200views Multimedia» more  MIR 2006»
15 years 3 months ago
An adaptive graph model for automatic image annotation
Automatic keyword annotation is a promising solution to enable more effective image search by using keywords. In this paper, we propose a novel automatic image annotation method b...
Jing Liu, Mingjing Li, Wei-Ying Ma, Qingshan Liu, ...
LREC
2010
148views Education» more  LREC 2010»
14 years 11 months ago
Tag Dictionaries Accelerate Manual Annotation
Expert human input can contribute in various ways to facilitate automatic annotation of natural language text. For example, a part-of-speech tagger can be trained on labeled input...
Marc Carmen, Paul Felt, Robbie Haertel, Deryle Lon...