STOCHASTIC PROCESS: Related Papers in ACL Anthology

STOCHASTIC PROCESS can be found in the following ACL ARC 1.0 documents (click to explore):

• (ACL ID: C00-1010) an empirical evaluation of lfg-dop
• (ACL ID: C00-2099) a statistical theory of dependency syntax
• (ACL ID: C69-4901) simulation of word-meaning stochastic processes
• (ACL ID: C96-1087) a probabilistic approach to compound noun indexing in korean texts
• (ACL ID: H89-2026) a stack decoder for continous speech recognition
• (ACL ID: H90-1087) large vocabulary speech recognition prototype
• (ACL ID: H92-1036) map estimation of continuous density hmm
• (ACL ID: H93-1023) topic and speaker identification via large vocabulary continuous speech recognition
• (ACL ID: H94-1053) statistical language processing using hidden understanding models
• (ACL ID: H94-1054) japanese word segmentation by hidden markov model
• (ACL ID: H94-1087) language identification via large vocabulary speaker independent continuous speech recognition
• (ACL ID: J03-4003) head-driven statistical models for natural language parsing
• (ACL ID: J05-2004) a mathematical model of historical semantics and the grouping of word meanings into concepts
• (ACL ID: J92-1002) an estimate of an upper bound for the entropy of english
• (ACL ID: J93-1007) retrieving collocations from text
• (ACL ID: J99-4005) squibs and discussions
• (ACL ID: N01-1021) a probabilistic earley parser as a psycholinguistic model
• (ACL ID: N03-1014) inducing history representations for broad coverage statistical parsing
• (ACL ID: N04-4010) using n-best lists for named entity recognition from chinese speech
• (ACL ID: P00-1009) an improved parser for data-oriented lexical-functional analysis
• (ACL ID: P01-1030) fast decoding and optimal decoding for machine translation
• (ACL ID: P01-1050) towards a unified approach to memory- and statistical-based machine translation
• (ACL ID: P03-1036) unsupervised segmentation of words using prior distributions of morph length and frequency
• (ACL ID: P04-1066) improving ibm word alignment model 1
• (ACL ID: P05-1042) a dynamic bayesian framework to model context and memory in edit distance learning
• (ACL ID: P05-1056) using conditional random fields for sentence boundary detection in speech
• (ACL ID: P06-1037) guiding a constraint dependency parser with supertags
• (ACL ID: P06-1085) contextual dependencies in unsupervised word segmentation
• (ACL ID: P06-2016) techniques to incorporate the benefits of a hierarchy in a modified hidden markov model
• (ACL ID: P91-1035) a stochastic process for word frequency distributions
• (ACL ID: P93-1042) how do we count? the problem of tagging phrasal verbs in parts
• (ACL ID: P94-1004) hidden understanding models of natural language
• (ACL ID: P96-1040) the rhythm of lexical stress in prose
• (ACL ID: P98-1022) a probabilistic corpus-driven model for lexical-functional analysis
• (ACL ID: P99-1070) relating probabilistic grammars and automata
• (ACL ID: W03-0302) proalign
• (ACL ID: W03-1012) using ltag based features in parse reranking
• (ACL ID: W03-1203) combining optimal clustering and hidden markov models for extractive summarization
• (ACL ID: W04-0104) automatic acquisition of feature-based phonotactic resources
• (ACL ID: W04-3209) comparing and combining generative and posterior probability models
• (ACL ID: W06-1606) spmt
• (ACL ID: W97-0304) text segmentation using exponential models
• (ACL ID: W97-1010) learning stochastic categorial grammars
• (ACL ID: W98-0805) the value of minimal prosodic information in spoken language corpora
• (ACL ID: W98-1105) semantic tagging using a probabilistic context free grammar
• (ACL ID: W98-1304) robust parsing using a hidden markov model
• (ACL ID: W99-0901) hiding a semantic hierarchy in a markov model