... paper, we formulate ex-
tractive summarization as a two step learn-
ing problem building a generative model
for pattern discovery and a regression
model for inference. We calculate scores
for sentences ... approaches for MDS as
presented in this paper.
In this paper, we present a novel approach that
formulates MDS as a prediction problem based
on a two-step hybrid model: a gen...
... of the Association for Computational Linguistics, pages 1367–1375,
Uppsala, Sweden, 11-16 July 2010.
c
2010 Association for Computational Linguistics
A Unified Graph Model for Sentence-based ... relevant to the target concerned.
Therefore, we argue that existing information
representation i.e. bag-of-word, cannot satisfy
the information needs for opinion retrieval.
In this pape...
... same form as the experimentalists so we in-
herit their careful design.
In this study, a total of 76 sentences were tested:
10 for lexical category ambiguity, 12 for RR am-
biguity, 20 for PP ... interpretation of the model for human
sentence processing. Corley and Crocker clearly
state that their model is strictly limited to lexical
ambiguity resolution, and their test of the mo...
... 61–64,
Prague, June 2007.
c
2007 Association for Computational Linguistics
A Joint Statistical Model for Simultaneous Word Spacing and
Spelling Error Correction for Korean
Hyungjong Noh* Jeong-Won ... network
8
4 Experiments and Analyses
4.1 Corpus Information
Table 1: Corpus information
Table 1 shows the information of corpus which is
used for experiments. All corpora ar...
... June 2005.
c
2005 Association for Computational Linguistics
A Phonotactic Language Model for Spoken Language Identification
Haizhou Li and Bin Ma
Institute for Infocomm Research
Singapore ... acoustic to-
kens to form a unified acoustic vocabulary in our
voice tokenizer. Readers are referred to (Ma
et al.
,
2005) for details of acoustic modeling.
3.1 Vector Space Modeling...
... blocks for for which
.
560
4 Online Training of Maximum-entropy
Model
The local model described in Section 3 leads to the fol-
lowing abstract maximum entropy training formulation:
(8)
In this formulation, ... is
obtained for this model. The ’SWAP & OR’ model uses
an orientation model as described in Section 3. Here, we
obtain a small but significant improvement over the base-...
... cues for repair processing.
Discussion
In this paper, we have presented a"speech-first" model,
the Repair Interval Model, for studying repairs in spon-
taneous speech. This model ...
AROA Air Travel Information System (ATIS) database.
Our results are interpreted within our "speech-first"
framework for investigating repairs, the REPAIR IN-
TERVAL MODEL (...
... each feture. ALL: all features,
PER: perceptron model, WLM: word language model,
PLM: POS language model, GPR: generating model,
LPR: labelling model, LEN: word count penalty.
LM with Witten-Bell ... algorithm.
1: Input: character sequence C
1:n
2: for i ← 1 n do
3: L ← ∅
4: for l ← 1 min(i, K) do
5: w ← C
i−l+1:i
6: for t ∈ P OS do
7: p ← label w as t
8: for q ∈ V[i − l] do
9:...
... calculation formulas are similar
with equations (13) and (14) respectively.
Before training trigram model (3), all possible
baseNP rules should be extracted from the
training corpus. For instance, ... describe the two-pass
statistical model, parameters training and Viterbi
algorithm for the search of the best sequences of
POS tagging and baseNP identification. Before
describing our alg...
... achieves an f-score of for EDU
identification, for identifying hierarchical spans, for
nuclearity identification and for relation tagging.
Parser
Discourse
Syntax
Parser
Forest
Generator
Decoder
Chooser
Length
Output ... is characterized by a rhetor-
ical relation. For example, the first sentence in
Text (1) provides BACKGROUND information for inter-
preting the information in senten...