unsupervised language model adaptation
Tài liệu Báo cáo khoa học: "Translation Model Adaptation for Statistical Machine Translation with Monolingual Topic Information" doc
Ngày tải lên :
19/02/2014, 19:20
... transferred across languages, to cross-
lingual language modeling and translation lexicon
adaptation. Recently, Gong and Zhou (2010) also
applied topic modeling into domain adaptation in
SMT. ... weblog.
According to adaptation emphases, domain adap-
tation in SMT can be classified into translation mod-
el adaptation and language model adaptation. Here
we focus on how to adapt a translation model, which
is ... Vogel.
2006. Distributed Language Modeling for N-best List
Re-ranking. In Proc. of EMNLP 2006, pages 216-223.
Bing Zhao, Matthias Eck and Stephan Vogel. 2004.
Language Model Adaptation for Statistical...
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Tài liệu Báo cáo khoa học: "Topic Models for Dynamic Translation Model Adaptation" pptx
Ngày tải lên :
19/02/2014, 19:20
... 2003). Topic
modeling has received some use in SMT, for in-
stance Bilingual LSA adaptation (Tam et al., 2007),
and the BiTAM model (Zhao and Xing, 2006),
which uses a bilingual topic model for ... Korea, 8-14 July 2012.
c
2012 Association for Computational Linguistics
Topic Models for Dynamic Translation Model Adaptation
Vladimir Eidelman
Computer Science
and UMIACS
University of Maryland
College ... topic-specific contexts, where
topics are induced in an unsupervised way
using topic models; this can be thought of
as inducing subcorpora for adaptation with-
out any human annotation. We use these...
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Tài liệu Báo cáo khoa học: "A Large Scale Distributed Syntactic, Semantic and Lexical Language Model for Machine Translation" doc
Ngày tải lên :
20/02/2014, 04:20
... 5-gram/2-SLM+2-gram/4-SLM+5-
gram/PLSA language model improves both signif-
icantly. Bear in mind that Charniak et al. (2003) in-
tegrated Charniak’s language model with the syntax-
based translation model Yamada and ... Large language models in ma-
chine translation. The 2007 Conference on Empirical
Methods in Natural Language Processing (EMNLP),
858-867.
E. Charniak. 2001. Immediate-head parsing for language
models. ... Dis-
tributed language modeling for N-best list re-ranking.
The 2006 Conference on Empirical Methods in Natu-
ral Language Processing (EMNLP), 216-223.
Y. Zhang, 2008. Structured language models for...
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Tài liệu Báo cáo khoa học: "Smoothing a Tera-word Language Model" doc
Ngày tải lên :
20/02/2014, 09:20
... Goodman. 2001. A bit of progress in language
modeling. Computer Speech and Language.
R. Kneser and H. Ney. 1995. Improved backing-off for
m-gram language modeling. In International Confer-
ence ... Bauman Peto. 1995. A
hierarchical Dirichlet language model. Natural Lan-
guage Engineering, 1(3):1–19.
Y.W. Teh. 2006. A hierarchical Bayesian language
model based on Pitman-Yor processes. In Proceed-
ings ... sure the probabilities are normalized. The
interpolated models always incorporate the lower or-
der distribution Pr(c|b) whereas the back-off models
consider it only when the n-gram abc has not been
observed...
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Tài liệu Báo cáo khoa học: "A Succinct N-gram Language Model" ppt
Ngày tải lên :
20/02/2014, 09:20
... -gram language models are com-
pressed into 10 GB, which is comparable to a lossy
representation (Talbot and Brants, 2008).
2 N -gram Language Model
We assume a back-off N-gram language model ... language model structure and word iden-
tifiers. In Proc. of ICASSP 2003, volume 1.
A. Stolcke. 1998. Entropy-based pruning of backoff
language models. In Proc. of the ARPA Workshop
on Human Language ... representation with
block compression. N-gram language models of
42.65GB were compressed to 18.37GB. Finally,
the 8-bit quantized N -gram language models are
represented by 9.83GB of space.
Table...
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Tài liệu Báo cáo khoa học: "A Phonotactic Language Model for Spoken Language Identification" pptx
Ngày tải lên :
20/02/2014, 15:20
... statistical language modeling,
and language identification. A typical LID system
is illustrated in Figure 1 (Zissman, 1996), where
language dependent voice tokenizers (VT) and lan-
guage models ... Tokenization at different resolutions
2.2 n-gram Language Model
With the sequence of tokens, we are able to es-
timate an n-gram language model (LM) from the
statistics. It is generally agreed ...
the 1996 NIST Language Recognition
Evaluation database.
1 Introduction
Spoken language and written language are similar
in many ways. Therefore, much of the research in
spoken language identification,...
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Tài liệu Báo cáo khoa học: "Japanese OCR Error Correction using Character Shape Similarity and Statistical Language Model " pptx
Ngày tải lên :
20/02/2014, 18:20
... efficient.
5
Experiments
5.1 Training Data for the Language
Model
We used the EDR Japanese Corpus Version 1.0
(EDR, 1991) to train the language model. It is a
corpus of approximately 5.1 million ... dictionary.
3.2 Word Model for Unknown Words
We defined a statistical word model to assign a rea-
sonable word probability to an arbitrary substring
in the input sentence. The word model is formally ... correction
candidate is selected by the word segmentation algo-
rithm using the OCR model and the language model.
For simplicity, we will present the method as if it
were for an isolated word...
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Tài liệu Báo cáo khoa học: "A Structured Language Model" ppt
Ngày tải lên :
22/02/2014, 03:20
... Derivational Model. In
Proceedings of the
Human Language Technology Workshop,
272-277.
ARPA.
Raymond Lau, Ronald Rosenfeld, and Salim
Roukos. 1993. Trigger-based language models: a
maximum ... 2 P(wk/Wk-ITk 1) = P(wjho)
models, re-
ferred to as H and h, respectively; h0 is the previous
exposed (headword, POS/non-term tag) pair; the
parses used in this model were those assigned man- ... word
wk
and they were
implemented using the Maximum Entropy Model-
ing Toolkit 1 (Ristad97). The constraint templates
in the {W,H} models were:
4 <= <*>_<*> <7>; P- <=...
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Báo cáo khoa học: "Intelligent Selection of Language Model Training Data" ppt
Ngày tải lên :
07/03/2014, 22:20
... domain-
specific and non-domain-specifc language
models, for each sentence of the text
source used to produce the latter language
model. We show that this produces better
language models, trained on less data, ... approach
to statistical language modeling for Chinese.
ACM Transactions on Asian Language Informa-
tion Processing, 1(1):3–33.
Dietrich Klakow. 2000. Selecting articles from
the language model training ... Chien,
Ker-Jiann Chen, and Lin-Shan Lee. 1997.
Chinese language model adaptation based on
document classification and multiple domain-
specific language models. In EUROSPEECH-
1997, 1463–1466.
Hermann...
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Báo cáo khoa học: "Optimizing Language Model Information Retrieval System with Expectation Maximization Algorithm" doc
Ngày tải lên :
08/03/2014, 01:20
... its original parame-
ters are given by the basic language modeling
approach calculation.
Figure 2. HMM model for EM IR
We define our HMM model as a four-tuple,
{S,A,B,π}, where S is a ... calculated with
the simple language modeling approach. Even if
the query term is not in the document, it will be
assigned a small value according to the basic
language modeling method. The rest ... states take
much time for one run, we firstly apply a basic
language modeling method to reduce our docu-
ment set. This language modeling method will be
detailed at Section 3.1. Based on the...
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Báo cáo khoa học: "A Discriminative Language Model with Pseudo-Negative Samples" pptx
Ngày tải lên :
08/03/2014, 02:21
... Discriminative Language Model with
Pseudo-Negative samples
We propose a novel discriminative language model;
a Discriminative Language Model with Pseudo-
Negative samples (DLM-PN). In this model,
pseudo-negative ... propose a novel discrim-
inative language model, which can be ap-
plied quite generally. Compared to the
well known N-gram language models, dis-
criminative language models can achieve
more accurate ... correctly.
2 Previous work
Probabilistic language models (PLMs) estimate the
probability of word strings or sentences. Among
these models, N-gram language models (NLMs) are
widely used. NLMs approximate...
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Báo cáo khoa học: "Language Model Based Arabic Word Segmentation" pdf
Ngày tải lên :
08/03/2014, 04:22
... involves (i)
language model training on a morpheme-
segmented corpus, (ii) segmentation of input
text into a sequence of morphemes using the
language model parameters, and (iii)
unsupervised ... inferred. We
would like to thank Martin Franz for discussions
on language model building, and his help with
the use of ViaVoice language model toolkit.
References
Beesley, K. 1996. Arabic Finite-State ... Prefix*-Stem-Suffix*
3 Morpheme Segmentation
3.1 Trigram Language Model
Given an Arabic sentence, we use a trigram
language model on morphemes to segment it
into a sequence of morphemes...
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Báo cáo khoa học: "Automatic Acquisition of Language Model based on Head-Dependent Relation between Words" pdf
Ngày tải lên :
08/03/2014, 05:21
... Preliminary experiments
We have experimented with three language
models, tri-gram model (TRI), bi-gram model
(BI), and the proposed model (DEP) on a raw
corpus extracted from KAIST corpus ... useful
than the naive word sequences of n-gram, for
language modeling.
We are planning to experiment the perfor-
mance of the proposed language model for large
corpus, for various domains, and ...
Based n-gram Models of Natural Language& quot;.
Computational Linguistics,
18(4):467-480.
C. Chang and C. Chen. 1996. "Application Is-
sues of SA-class Bigram Language Models"....
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Báo cáo khoa học: "A Preference-first Language Processor Integrating the Unification Grammar and Markov Language Model for Speech Recognition-ApplicationS" potx
Ngày tải lên :
08/03/2014, 07:20
... The language processor consists
of a language model and a parser. The language model
properly integrates the unification grammar and the
Markov language model, while the parser is defined
based ...
language processor has been developed and tested on a
small lexicon, a Markov language model, and a simple
set of unification grammar rules for the Chinese
language, although the present model ... summarized.
The Laneua~e Model
The goal of the language model is to participate
in the selection of candidate constituents for a
sentence to be identified. The proposed language
model is composed...
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Báo cáo khoa học: "Combining a Statistical Language Model with Logistic Regression to Predict the Lexical and Syntactic Difficulty of Texts for FFL" potx
Ngày tải lên :
08/03/2014, 21:20
... a
statistical language model and a measure of tense
difficulty.
4.1 The language model
The lexical difficulty of a text is quite an elaborate
phenomenon to parameterise. The logistic regres-
sion models ... linguistic unit to
consider. The equations introduced above use
21
6.1 The language model: probabilities and
smoothing
For our language model, we need a list of French
lemmas with their frequencies of ... B2 C1 C2 Mean
PO model 91% 91% 67% 68% 53% 55% 56% 86% 68% 70%
MLR model 93% 90% 69% 51% 59% 56% 64% 88% 73% 71%
Table 2: Mean adjacent accuracy per level for PO model and MLR model (on the test...
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