... 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 possibletrees to counting the number of spanning trees in agraph, it can be shown that Zxis the determinant of the Kirchoff matrix K, which is ... marginalprobability of a particular edge k → i (i.e. yi=k),the score of any edge k→ i such that k= k isset to 0. The determinant of the resulting modi-fied Kirchoff matrix Kk→iis then the sum of ... basictypes of linguistic knowledge.One simple form of linguistic knowledge is theset of possible parent tags for a given child tag.This type of constraint was used in the devel-opment of a rule-based...
... tractableamount of time, since according to the Markov as-2Often these are more complicated than picking informativefeatures as proposed in this paper. One example of the kind of operator used ... Semi-Supervised Learning of Conditional Random FieldsGideon S. MannGoogle Inc.76 Ninth AvenueNew York, NY 10011Andrew McCallumDepartment of Computer ScienceUniversity of Massachusetts140 ... addition of lower cost unlabeled data. Tradi-tional approaches to semi-supervised learning areapplied 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 (T1, H1)and (T1, H2) have both the same intra-pair simi-larity since the sentences of T1and ... head of constituents. Theexample of Fig. 1 shows that the placeholder0climbs up to the node governing all the NPs.5.3 Pruning irrelevant information in largetext treesOften only a portion of ... t, the set of its nodes N (t), and a set of anchors, we builda tree twith all the nodes Nthat are anchors orancestors of any anchor. Moreover, we add to tthe 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-orderMST has a score of m. Proof: First we observe that no tr eecan have a score greater than m since that would require morethan m pairs of edges of t he form (xi, yj, zk). ... consist-ing of pairs of a sentence xtand its correct depen-dency representation yt.The algorithm is an extension of the Margin In-fused Relaxed Algorithm (MIRA) (Crammer andSinger, 2003) to learning ... investigate the benefitsfor parsing of more principled approaches to ap-proximate learning and inference techniques suchas the learning as search optimization framework of (Daum´e and Marcu, 2005)....
... Kallirroi Georgila, and James HendersonSchool of InformaticsUniversity of Edinburgholemon@inf.ed.ac.ukMatthew StuttleDept. of EngineeringUniversity of Cambridgemns25@cam.ac.ukAbstractWe demonstrate ... actionsand in-car dialo gue actions, for each sub-task type of the in-car system.121An ISU Dialogue System Exhibiting Reinforcement Learningof DialoguePolicies: Generic Slot-filling in the TALK ... to exhibit rein-forcement learningof dialogue strategies, andalso has a fragmentary clarification feature.This paper describes the main components andfunctionality of the system, as well as...
... candidates. Of the 740 cloze tests, 714 of theremoved events were present in their respective list of guesses. This is encouraging as only 3.5% of theevents are unseen (or do not meet cutoff thresholds).When ... thus a tuple of the event and thetyped dependency of the protagonist: (event, depen-dency). A narrative chain is a set of narrative events{e1, e2, , en}, where n is the size of the chain, ... specifically on learning narratives1, 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.2While the first gold standard dataset of verbpairs was annotated out of context, we constructeda 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 classificationstarts 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 asdescribed in Section 2. It is based on observingthat the improvement in the goodness of fit by upto two consecutive splits of any of the current HMMstates ... differ-ent learning setups are tabulated. We also see how aslittle as 5 minutes of speech is adequate for learning the acoustic units.2 An Improved and Fast SSS AlgorithmThe 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), pages255–262, July.John Goldsmith. 2001. Unsupervised learningof the morphology of a natural ... improvement of 22-38% in average precision over unstemmed text, and93-96% of the performance of the state of the art,language specific stemmer above.We can speculate that, because of the statisticalnature ... 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.ReferencesP....
... temperature dependence of the morphology of SiNWs synthesized by laser abla-tion. In this Letter, we present the results on thisproject. Our results show that the morphology anddiameter of SiNWs synthesized ... silicon nanoparticle chains of smaller diameters inhigher 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 Geinto Si can reduce the melting point of the siliconsolid 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 theiteration of the following two steps:• (DE learning) Apply DLD09 using a set N of pseudo-NPIs to retrieve a list of candidateDE operators ... consequence of the very small size of the NPIlist employed, and may therefore indicate that itwould 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 xare then ranked byfr(x) :=fraction of DE contexts that contain xrelative frequency of x in...
... confidence-weighted learning, a form of discriminative online learning that can bettertake advantage of a heavy tail of rare features.Finally, we extend the confidence-weighted learning to deal ... features,confidence-weighted learning is slightly better thanperceptron, and confidence-weighted learning withsoft margin is the best (9.08% and 5.04% better thanperceptron and confidence-weighted learning withhard ... Katrin Kirchhoff. 2003. Fac-tored language models and generalized parallel back-off. In Proceedings of HLT/NAACL, Edmonton, Al-berta, Canada.Koby Crammer and Daniel D. Lee. 2010. Learning viagaussian...