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Improving nonparameteric Bayesian inference: experiments on unsupervised word segmentation with adaptor grammars
Mark Johnson
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Sharon Goldwater
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Paper Details:
Month: June
Year: 2009
Location: Boulder, Colorado
Venue:
NAACL |
Citations
URL
Unsupervised phonemic Chinese word segmentation using Adaptor Grammars
Mark Johnson
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Katherine Demuth
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Unsupervised Word Segmentation in Context
Gabriel Synnaeve
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Isabelle Dautriche
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Benjamin Börschinger
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Mark Johnson
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Emmanuel Dupoux
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Fast Collocation-Based Bayesian HMM Word Alignment
Philip Schulz
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Wilker Aziz
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Modeling Perspective Using Adaptor Grammars
Eric Hardisty
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Jordan Boyd-Graber
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Philip Resnik
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An Efficient Algorithm for Unsupervised Word Segmentation with Branching Entropy and MDL
Valentin Zhikov
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Hiroya Takamura
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Manabu Okumura
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Iterative Annotation Transformation with Predict-Self Reestimation for Chinese Word Segmentation
Wenbin Jiang
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Fandong Meng
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Qun Liu
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Yajuan Lü
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Adaptor Grammars for Learning Non-Concatenative Morphology
Jan A. Botha
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Phil Blunsom
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Syllable weight encodes mostly the same information for English word segmentation as dictionary stress
John K Pate
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Mark Johnson
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Speech segmentation with a neural encoder model of working memory
Micha Elsner
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Cory Shain
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Incorporating Lexical Priors into Topic Models
Jagadeesh Jagarlamudi
|
Hal Daumé III
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Raghavendra Udupa
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Bridging the gap between speech technology and natural language processing: an evaluation toolbox for term discovery systems
Bogdan Ludusan
|
Maarten Versteegh
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Aren Jansen
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Guillaume Gravier
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Xuan-Nga Cao
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Mark Johnson
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Emmanuel Dupoux
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Learning Words and Their Meanings from Unsegmented Child-directed Speech
Bevan K. Jones
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Mark Johnson
|
Michael C. Frank
|
Subword Variation in Text Message Classification
Robert Munro
|
Christopher D. Manning
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Variational Inference for Adaptor Grammars
Shay B. Cohen
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David M. Blei
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Noah A. Smith
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Painless Unsupervised Learning with Features
Taylor Berg-Kirkpatrick
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Alexandre Bouchard-Côté
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John DeNero
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Dan Klein
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A Systematic Bayesian Treatment of the IBM Alignment Models
Yarin Gal
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Phil Blunsom
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Sign constraints on feature weights improve a joint model of word segmentation and phonology
Mark Johnson
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Joe Pater
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Robert Staubs
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Emmanuel Dupoux
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Prosodic boundary information helps unsupervised word segmentation
Bogdan Ludusan
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Gabriel Synnaeve
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Emmanuel Dupoux
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PCFGs, Topic Models, Adaptor Grammars and Learning Topical Collocations and the Structure of Proper Names
Mark Johnson
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Blocked Inference in Bayesian Tree Substitution Grammars
Trevor Cohn
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Phil Blunsom
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Insertion Operator for Bayesian Tree Substitution Grammars
Hiroyuki Shindo
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Akinori Fujino
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Masaaki Nagata
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Bayesian Symbol-Refined Tree Substitution Grammars for Syntactic Parsing
Hiroyuki Shindo
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Yusuke Miyao
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Akinori Fujino
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Masaaki Nagata
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Exploiting Social Information in Grounded Language Learning via Grammatical Reduction
Mark Johnson
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Katherine Demuth
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Michael Frank
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Using Rejuvenation to Improve Particle Filtering for Bayesian Word Segmentation
Benjamin Börschinger
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Mark Johnson
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Unsupervised Morphology Rivals Supervised Morphology for Arabic MT
David Stallard
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Jacob Devlin
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Michael Kayser
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Yoong Keok Lee
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Regina Barzilay
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A Markov Model of Machine Translation using Non-parametric Bayesian Inference
Yang Feng
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Trevor Cohn
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Discriminative Learning with Natural Annotations: Word Segmentation as a Case Study
Wenbin Jiang
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Meng Sun
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Yajuan Lü
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Yating Yang
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Qun Liu
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A joint model of word segmentation and phonological variation for English word-final /t/-deletion
Benjamin Börschinger
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Mark Johnson
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Katherine Demuth
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An improved MDL-based compression algorithm for unsupervised word segmentation
Ruey-Cheng Chen
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Modelling function words improves unsupervised word segmentation
Mark Johnson
|
Anne Christophe
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Emmanuel Dupoux
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Katherine Demuth
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Joint Word Segmentation and Phonetic Category Induction
Micha Elsner
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Stephanie Antetomaso
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Naomi Feldman
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Word Alignment without NULL Words
Philip Schulz
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Wilker Aziz
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Khalil Sima’an
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Minimally-Supervised Morphological Segmentation using Adaptor Grammars
Kairit Sirts
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Sharon Goldwater
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Exploring the Role of Stress in Bayesian Word Segmentation using Adaptor Grammars
Benjamin Börschinger
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Mark Johnson
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Online Adaptor Grammars with Hybrid Inference
Ke Zhai
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Jordan Boyd-Graber
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Shay B. Cohen
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Unsupervised Lexicon Discovery from Acoustic Input
Chia-ying Lee
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Timothy J. O’Donnell
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James Glass
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A Generative Model of Phonotactics
Richard Futrell
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Adam Albright
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Peter Graff
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Timothy J. O’Donnell
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Learning Semantics and Selectional Preference of Adjective-Noun Pairs
Karl Moritz Hermann
|
Chris Dyer
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Phil Blunsom
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Stephen Pulman
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Do POS Tags Help to Learn Better Morphological Segmentations?
Kairit Sirts
|
Mark Johnson
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Recession Segmentation: Simpler Online Word Segmentation Using Limited Resources
Constantine Lignos
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Charles Yang
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Modeling Infant Word Segmentation
Constantine Lignos
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A Regularized Compression Method to Unsupervised Word Segmentation
Ruey-Cheng Chen
|
Chiung-Min Tsai
|
Jieh Hsiang
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Why is English so easy to segment?
Abdellah Fourtassi
|
Benjamin Börschinger
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Mark Johnson
|
Emmanuel Dupoux
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An explicit statistical model of learning lexical segmentation using multiple cues
Çağrı Çöltekin
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John Nerbonne
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Weakly-Supervised Bayesian Learning of a CCG Supertagger
Dan Garrette
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Chris Dyer
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Jason Baldridge
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Noah A. Smith
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Units in segmentation: a computational investigation
Çağrı Çöltekin
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Joint Bayesian Morphology Learning for Dravidian Languages
Arun Kumar
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Lluís Padró
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Antoni Oliver
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Learning Phone Embeddings for Word Segmentation of Child-Directed Speech
Jianqiang Ma
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Çağrı Çöltekin
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Erhard Hinrichs
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Adaptor Grammars for the Linguist: Word Segmentation Experiments for Very Low-Resource Languages
Pierre Godard
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Laurent Besacier
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François Yvon
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Martine Adda-Decker
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Gilles Adda
|
Hélène Maynard
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Annie Rialland
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http://www.cog.brown.edu/mj/Software.htm
Field Of Study
Task
Word Segmentation
Approach
Bayesian Model
Language
Chinese
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