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A Joint Learning Model of Word Segmentation, Lexical Acquisition, and Phonetic Variability
Micha Elsner
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Sharon Goldwater
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Naomi Feldman
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Frank Wood
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Paper Details:
Month: October
Year: 2013
Location: Seattle, Washington, USA
Venue:
EMNLP |
SIG: SIGDAT
Citations
URL
Bayesian Language Model based on Mixture of Segmental Contexts for Spontaneous Utterances with Unexpected Words
Ryu Takeda
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Kazunori Komatani
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Unsupervised Segmentation of Phoneme Sequences based on Pitman-Yor Semi-Markov Model using Phoneme Length Context
Ryu Takeda
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Kazunori Komatani
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DIMSIM: An Accurate Chinese Phonetic Similarity Algorithm Based on Learned High Dimensional Encoding
Min Li
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Marina Danilevsky
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Sara Noeman
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Yunyao Li
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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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Weak semantic context helps phonetic learning in a model of infant language acquisition
Stella Frank
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Naomi H. Feldman
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Sharon Goldwater
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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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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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Modeling Word Forms Using Latent Underlying Morphs and Phonology
Ryan Cotterell
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Nanyun Peng
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Jason Eisner
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Segmentation and UR Acquisition with UR Constraints
Max Nelson
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https://bitbucket.org/
Field Of Study
Linguistic Trends
Phonology
Phonetics
Task
Word Segmentation
Approach
Bayesian Model
Graphical Model
Unsupervised Learning
Language
English
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