... the theories of second language learning:
definitions of language acquisition and theoretical background of language learning factors
in specific such as intelligence, personality, learning strategies, ... well as environment and context of learning.
2.2. Definitions of language acquisition
“Language acquisition is one of the most impressive and fascinating aspects of
human development” (Lightbown, ... process of the first language learning can be better understood if the social
dimension is included. Social factors have even more importance in the case of second
language learning because of the...
... x.
By relating the sum of the scores of all possible
trees to counting the number of spanning trees in a
graph, it can be shown that Z
x
is the determinant
of the Kirchoff matrix K, which is ... marginal
probability of a particular edge k → i (i.e. y
i
=k),
the score of any edge k
→ i such that k
= k is
set to 0. The determinant of the resulting modi-
fied Kirchoff matrix K
k→i
is then the sum of ... basic
types of linguistic knowledge.
One simple form of linguistic knowledge is the
set of possible parent tags for a given child tag.
This type of constraint was used in the devel-
opment of a rule-based...
... tractable
amount of time, since according to the Markov as-
2
Often these are more complicated than picking informative
features as proposed in this paper. One example of the kind of
operator used ... Semi-Supervised Learning of
Conditional Random Fields
Gideon S. Mann
Google Inc.
76 Ninth Avenue
New York, NY 10011
Andrew McCallum
Department of Computer Science
University of Massachusetts
140 ... addition of lower cost unlabeled data. Tradi-
tional approaches to semi-supervised learning are
applied to cases in which there is a small amount of
fully labeled data and a much larger amount of un-
labeled...
... ex-
amples of the previous section. From the point of
view of bag -of- word methods, the pairs (T
1
, H
1
)
and (T
1
, H
2
) have both the same intra-pair simi-
larity since the sentences of T
1
and ... head of constituents. The
example of Fig. 1 shows that the placeholder
0
climbs up to the node governing all the NPs.
5.3 Pruning irrelevant information in large
text trees
Often only a portion of ... t, the set
of its nodes N (t), and a set of anchors, we build
a tree t
with all the nodes N
that are anchors or
ancestors of any anchor. Moreover, we add to t
the leaf nodes of the original...
... algorithm to perform WSD on a set of
polysemous English words. They report an accu-
racy of 74%.
One of the most active researchers in identify-
ing cognates between pairs of languages is
Kondrak ... we
show that nonetheless machines are capable of
learning from new information, using an iterative
approach, similar to the learning process of hu-
mans. New information was collected and ... Studies of Intelligence, pp.44-
59.
Grzegorz Kondrak. 2001. Identifying Cognates by
Phonetic and Semantic Similarity. Proceedings of
NAACL 2001: 2nd Meeting of the North American
Chapter of the...
... the second-order
MST has a score of m. Proof: First we observe that no tr ee
can have a score greater than m since that would require more
than m pairs of edges of t he form (x
i
, y
j
, z
k
). ... consist-
ing of pairs of a sentence x
t
and its correct depen-
dency representation y
t
.
The algorithm is an extension of the Margin In-
fused Relaxed Algorithm (MIRA) (Crammer and
Singer, 2003) to learning ... investigate the benefits
for parsing of more principled approaches to ap-
proximate learning and inference techniques such
as the learning as search optimization framework
of (Daum´e and Marcu, 2005)....
... Kallirroi Georgila, and James Henderson
School of Informatics
University of Edinburgh
olemon@inf.ed.ac.uk
Matthew Stuttle
Dept. of Engineering
University of Cambridge
mns25@cam.ac.uk
Abstract
We demonstrate ... actions
and in-car dialo gue actions, for each sub-task type of
the in-car system.
121
An ISU Dialogue System Exhibiting Reinforcement Learningof Dialogue
Policies: Generic Slot-filling in the TALK ... to exhibit rein-
forcement learningof dialogue strategies, and
also has a fragmentary clarification feature.
This paper describes the main components and
functionality of the system, as well as...
... candidates. Of the 740 cloze tests, 714 of the
removed events were present in their respective list
of guesses. This is encouraging as only 3.5% of the
events are unseen (or do not meet cutoff thresholds).
When ... thus a tuple of the event and the
typed dependency of the protagonist: (event, depen-
dency). A narrative chain is a set of narrative events
{e
1
, e
2
, , e
n
}, where n is the size of the chain, ... specifically on
learning narratives
1
, our work draws from two lines
of research in summarization and anaphora resolu-
tion. In summarization, topic signatures are a set
of terms indicative of a topic...
... difficulty of decision in the annotation
of fine-grained semantic relations.
2
While the first gold standard dataset of verb
pairs was annotated out of context, we constructed
a second gold standard of ... understudied in the field of corpus-based
learning of semantic relations. Machine learning
methods have been previously applied to deter-
mine semantic relations such as is-a and part -of,
also succession, ... Classifiers in Ensemble Learning.
Both token-based and type-based classification
starts with determining of the most confident clas-
sification for instances. Each instance of the cor-
pus of unlabeled verb...
... im-
provement in the efficacy of the SSS algorithm as
described in Section 2. It is based on observing
that the improvement in the goodness of fit by up
to two consecutive splits of any of the current HMM
states ... differ-
ent learning setups are tabulated. We also see how as
little as 5 minutes of speech is adequate for learning
the acoustic units.
2 An Improved and Fast SSS Algorithm
The improvement of the ... that the original application of SSS was for learning
Figure 1: Modified four-way split of a state s.
2. For each HMM state s, compute the gain in log-
likelihood (LL) of the speech by either a con-
textual...
... Proceedings of the 40th Annual Meeting of the As-
sociation for Computational Linguistics (ACL), pages
255–262, July.
John Goldsmith. 2001. Unsupervised learningof the
morphology of a natural ... improvement of 22-
38% in average precision over unstemmed text, and
93-96% of the performance of the state of the art,
language specific stemmer above.
We can speculate that, because of the statistical
nature ... views,
conclusions and findings in this paper are those of
the authors and do not necessarily reflect the posi-
tion of policy of the Government and no of cial en-
dorsement should be inferred.
References
P....
... temperature dependence of the
morphology of SiNWs synthesized by laser abla-
tion. In this Letter, we present the results on this
project. Our results show that the morphology and
diameter of SiNWs synthesized ... silicon nanoparticle chains of smaller diameters in
higher temperature zone (960–1120 °C). The distribution of the morphology and diameter of SiNWs as a function of
growth temperature differs ... addition of Mg and Ge
into Si can reduce the melting point of the silicon
solid solution. Moreover, the melting points of
nanoparticles are usually lower than the corre-
sponding bulk material. All of...
... corpus
.
Then, our co -learning algorithm consists of the
iteration of the following two steps:
• (DE learning) Apply DLD09 using a set N
of pseudo-NPIs to retrieve a list of candidate
DE operators ... consequence of the very small size of the NPI
list employed, and may therefore indicate that it
would be fruitful to investigate automatically ex-
tending our list of clues.
3.4 Main idea: a co -learning ... right of a DE operator, up to the first comma,
semi-colon or end of sentence); these candidates x
are then ranked by
f
r
(x) :=
fraction of DE contexts that contain x
relative frequency of x in...
... confidence-weighted learning, a form of
discriminative online learning that can better
take advantage of a heavy tail of rare features.
Finally, we extend the confidence-weighted
learning to deal ... features,
confidence-weighted learning is slightly better than
perceptron, and confidence-weighted learning with
soft margin is the best (9.08% and 5.04% better than
perceptron and confidence-weighted learning with
hard ... Katrin Kirchhoff. 2003. Fac-
tored language models and generalized parallel back-
off. In Proceedings of HLT/NAACL, Edmonton, Al-
berta, Canada.
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gaussian...