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ACL
2006
13 years 6 months ago
Morphological Richness Offsets Resource Demand - Experiences in Constructing a POS Tagger for Hindi
In this paper we report our work on building a POS tagger for a morphologically rich language- Hindi. The theme of the research is to vindicate the stand that- if morphology is st...
Smriti Singh, Kuhoo Gupta, Manish Shrivastava, Pus...
LREC
2008
85views Education» more  LREC 2008»
13 years 6 months ago
Detecting Errors in Semantic Annotation
We develop a method for detecting errors in semantic predicate-argument annotation, based on the variation n-gram error detection method. After establishing an appropriate data re...
Markus Dickinson, Chong Min Lee
SIGDIAL
2010
13 years 3 months ago
Online Error Detection of Barge-In Utterances by Using Individual Users' Utterance Histories in Spoken Dialogue System
We develop a method to detect erroneous interpretation results of user utterances by exploiting utterance histories of individual users in spoken dialogue systems that were deploy...
Kazunori Komatani, Hiroshi G. Okuno
ICANN
2001
Springer
13 years 9 months ago
On-Line Error Detection of Annotated Corpus Using Modular Neural Networks
This paper proposes an on-line error detecting method for a manually annotated corpus using min-max modular (M3 ) neural networks. The basic idea of the method is to use guaranteed...
Qing Ma, Bao-Liang Lu, Masaki Murata, Michinori Ic...
EACL
2003
ACL Anthology
13 years 6 months ago
Detecting Errors in Part-of-Speech Annotation
We propose a new method for detecting errors in “gold-standard” part-ofspeech annotation. The approach locates errors with high precision based on n-grams occurring in the cor...
Markus Dickinson, Detmar Meurers