smoothing ngram language models
Tài liệu Báo cáo khoa học: "Improved Smoothing for N-gram Language Models Based on Ordinary Counts" doc
Ngày tải lên :
20/02/2014, 09:20
... USA
{bobmoore,chrisq}@microsoft.com
Abstract
Kneser-Ney (1995) smoothing and its vari-
ants are generally recognized as having
the best perplexity of any known method
for estimating N-gram language models.
Kneser-Ney smoothing, however, ... Kneser-Ney and
those methods.
1 Introduction
Statistical language models are potentially useful
for any language technology task that produces
natural -language text as a final (or intermediate)
output. ... lower-
order models used to smooth the highest-
order model. For some applications, this
makes Kneser-Ney smoothing inappropri-
ate or inconvenient. In this paper, we in-
troduce a new smoothing...
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Tài liệu Báo cáo khoa học: "Incremental Syntactic Language Models for Phrase-based Translation" pptx
Ngày tải lên :
20/02/2014, 04:20
... sequence
models as language models.
Modern phrase-based translation using large scale
n-gram language models generally performs well
in terms of lexical choice, but still often produces
ungrammatical ... to incorporate large-
scale n-gram language models in conjunction with
incremental syntactic language models.
The added decoding time cost of our syntactic
language model is very high. By increasing ... Jelinek. 2000. Structured
language modeling. Computer Speech and Language,
14(4):283–332.
Stanley F. Chen and Joshua Goodman. 1998. An empir-
ical study of smoothing techniques for language mod-
eling....
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Tài liệu Báo cáo khoa học: "The impact of language models and loss functions on repair disfluency detection" pptx
Ngày tải lên :
20/02/2014, 04:20
... language
models trained from text or speech corpora of vari-
ous genres and sizes. The largest available language
models are based on written text: we investigate the
effect of written text language models ... dif-
ferences among the different language models when
extended features are present are relatively small.
We assume that much of the information expressed
in the language models overlaps with the lexical ... information from
the external language models by defining a reranker
feature for each external language model. The value
of this feature is the log probability assigned by the
language model to the candidate...
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Tài liệu Báo cáo khoa học: "An Empirical Investigation of Discounting in Cross-Domain Language Models" ppt
Ngày tải lên :
20/02/2014, 04:20
... of English
Bigrams. Computer Speech & Language, 5(1):19–54.
Joshua Goodman. 2001. A Bit of Progress in Language
Modeling. Computer Speech & Language, 15(4):403–
434.
Bo-June (Paul) Hsu ... Short Papers, pages
220–224, July.
Robert C. Moore and Chris Quirk. 2009. Improved
Smoothing for N-gram Language Models Based on
Ordinary Counts. In Proceedings of the ACL-IJCNLP
2009 Conference ... 2006. MAP adaptation of stochastic
grammars. Computer Speech & Language, 20(1):41 –
68.
Jerome R. Bellegarda. 2004. Statistical language model
adaptation: review and perspectives. Speech Commu-
nication,...
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Tài liệu Báo cáo khoa học: "Reading Level Assessment Using Support Vector Machines and Statistical Language Models" pdf
Ngày tải lên :
20/02/2014, 15:20
... statistical language models.
In this paper, we also use support vector
machines to combine features from tradi-
tional reading level measures, statistical
language models, and other language pro-
cessing ... use scores from language models as
features in another classifier (e.g. an SVM). For ex-
ample, perplexity (P P) is an information-theoretic
measure often used to assess language models:
P P = 2
H(t|c)
, ... of syntax. Our approach uses n-
gram language models as a low-cost automatic ap-
proximation of both syntactic and semantic analy-
sis. Statistical language models (LMs) are used suc-
cessfully...
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Tài liệu Báo cáo khoa học: "Generating statistical language models from interpretation grammars in dialogue systems" potx
Ngày tải lên :
22/02/2014, 02:20
... comparison of in-
grammar recognition performance.
3 Language modelling
To generate the different trigram language models
we used the SRI language modelling toolkit (Stol-
cke, 2002) with Good-Turing ... decades of statistical language
modeling: Where do we go from here? In Proceed-
ings of IEEE:88(8).
Rosenfeld R. 2000. Incorporating Linguistic Structure
into Statistical Language Models. In Philosophical
Transactions ... statistical language models (DM-SLMs)
by using GF to generate all utterances that are
specific to certain dialogue moves from our in-
terpretation grammar. In this way we can pro-
duce models that...
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Tài liệu Báo cáo khoa học: "Web augmentation of language models for continuous speech recognition of SMS text messages" docx
Ngày tải lên :
22/02/2014, 02:20
... 2007. Large language
models in machine translation. In Proceedings
of the 2007 Joint Conference on Empirical Meth-
ods in Natural Language Processing and Com-
putational Natural Language Learning ... empirical
study of smoothing techniques for language model-
ing. Computer Speech and Language, 13:359–394.
Joshua T. Goodman. 2001. A bit of progress in lan-
guage modeling. Computer Speech and Language,
15:403–434.
Slava ... Kneser-
Ney smoothed n-gram models. IEEE Transac-
tions on Audio, Speech and Language Processing,
15(5):1617–1624.
A. Stolcke. 1998. Entropy-based pruning of backoff
language models. In Proc. DARPA...
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Báo cáo khoa học: "The use of formal language models in the typology of the morphology of Amerindian languages" potx
Ngày tải lên :
07/03/2014, 22:20
... grammars for modeling agglutination
in this language, but first we will present the for-
mer class of languages and its acceptor automata.
3.1 Linear context free languages and
two-taped nondeterministic ... 2010.
c
2010 Association for Computational Linguistics
The use of formal language models in the typology of the morphology of
Amerindian languages
Andr
´
es Osvaldo Porta
Universidad de Buenos Aires
hugporta@yahoo.com.ar
Abstract
The ... natural representa-
tion in terms of linear context-free languages.
2 Quichua Santiague
˜
no
The quichua santiague˜no is a language of the
Quechua language family. It is spoken in the San-
tiago del...
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Báo cáo khoa học: "Faster and Smaller N -Gram Language Models" pptx
Ngày tải lên :
07/03/2014, 22:20
... novel language model
caching technique that improves the query
speed of our language models (and SRILM)
by up to 300%.
1 Introduction
For modern statistical machine translation systems,
language models ... with two different language models.
Our first language model, WMT2010, was a 5-
gram Kneser-Ney language model which stores
probability/back-off pairs as values. We trained this
language model on ... and Smaller N -Gram Language Models
Adam Pauls Dan Klein
Computer Science Division
University of California, Berkeley
{adpauls,klein}@cs.berkeley.edu
Abstract
N-gram language models are a major...
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Báo cáo khoa học: "Enhancing Language Models in Statistical Machine Translation with Backward N-grams and Mutual Information Triggers" ppt
Ngày tải lên :
07/03/2014, 22:20
... or even trillions of English words,
huge language models are built in a distributed man-
ner (Zhang et al., 2006; Brants et al., 2007). Such
language models yield better translation results but
at ... explore a dependency language
model to improve translation quality. To some ex-
tent, these syntactically-informed language models
are consistent with syntax-based translation models
in capturing ... integrate backward n-grams and mu-
tual information (MI) triggers into language models
in SMT.
In conventional n-gram language models, we look
at the preceding n − 1 words when calculating the
probability...
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Báo cáo khoa học: "Randomized Language Models via Perfect Hash Functions" pptx
Ngày tải lên :
08/03/2014, 01:20
... (lossless) lan-
guages models and our randomized language model.
Note that the standard practice of measuring per-
plexity is not meaningful here since (1) for efficient
computation, the language model ... 2007.
Compressing trigram language models with golomb
coding. In Proceedings of EMNLP-CoNLL 2007,
Prague, Czech Republic, June.
P. Clarkson and R. Rosenfeld. 1997 . Statistical language
modeling using ... pruning of back-
off language models. In Proc. DARPA Broadcast News
Transcription and Understanding Workshop, pages
270–274.
D. Talbot and M. Osborne. 2007a. Randomised language
modelling for...
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Báo cáo khoa học: "Generalized Algorithms for Constructing Statistical Language Models" pdf
Ngày tải lên :
08/03/2014, 04:22
... .
Class-based models. In many applications, it is nat-
ural and convenient to construct class-based language
models, that is models based on classes of words (Brown
et al., 1992). Such models are ... the classical definitions of -
gram language models and several smoothing techniques
commonly used. We then describe a natural representa-
tion of -gram language models using failure transitions.
This ... experi-
mental results demonstrating its efficiency.
Representation of language models by WFAs. Clas-
sical
-gram language models admit a natural representa-
tion by WFAs in which each state encodes...
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Báo cáo khoa học: "Cutting the Long Tail: Hybrid Language Models for Translation Style Adaptation" doc
Ngày tải lên :
08/03/2014, 21:20
... Hoang. 2007. Factored
translation models. In Proceedings of the 2007
Joint Conference on Empirical Methods in Natural
Language Processing and Computational Natural
Language Learning (EMNLP-CoNLL), ... Monz. 2011. Statistical Machine Translation
with Local Language Models. In Proceedings of the
2011 Conference on Empirical Methods in Natural
Language Processing, pages 869–879, Edinburgh,
Scotland, ... (Tillmann, 2004; Koehn et al., 2005), two
word-based language models, distortion, word
and phrase penalties. The translation and re-
ordering models are obtained by combining mod-
els independently...
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Báo cáo khoa học: "Deciphering Foreign Language by Combining Language Models and Context Vectors" pdf
Ngày tải lên :
16/03/2014, 19:20
... Computational Linguistics
Deciphering Foreign Language by Combining Language Models and
Context Vectors
Malte Nuhn and Arne Mauser
∗
and Hermann Ney
Human Language Technology and Pattern Recognition ... to universally communi-
cate in all languages. In these visions, even previ-
ously unknown languages can be learned automati-
cally from analyzing foreign language input.
In this work, we attempt ... to learn statistical trans-
lation models from only monolingual data in the
source and target language. The reasoning behind
this idea is that the elements of languages share sta-
tistical similarities...
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Báo cáo khoa học: "Confidence-Weighted Learning of Factored Discriminative Language Models" pptx
Ngày tải lên :
17/03/2014, 00:20
... directions:
generative factored language model, discriminative
language models, online passive-aggressive learning
and confidence-weighted learning.
Generative factored language models are pro-
posed by ... Introduction
Language Models (LMs) are key components in
most statistical machine translation systems, where
they play a crucial role in promoting output fluency.
Standard n-gram generative language models
have ... learning language models,
we use confidence-weighted learning (Dredze et al.,
2008), an extension of the perceptron-based on-
line learning used in previous work on discrimi-
native language models. ...
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