The corpora of English-language parental child-directed speech represent the linguistic input that young children receive when acquiring syntax. Although each separate study is by necessity limited in its coverage of the phenomenon, the different studies pooled together can provide the requisite solid database for generalization. The use of pooled corpora of unrelated parents as a representation of the linguistic input is a relatively conventional move in child language research (e.g., Goodman et al., 2008). Multiple speakers of child-directed speech may provide a good estimate of the total linguistic input to which children are exposed, which includes, besides the speech of the individual mother or father, also the speech of grandparents, aunts and uncles, older siblings and other family members, neighbours, care professionals, and so forth, represented in our corpus by the speech of mothers and fathers unrelated to the individual child. The pooled database represents the language behaviour exhibited by the community as a whole when addressing young children.
Lourdes Ortega (2003) defines syntactic complexity as “the range of forms that surface in language production and the degree of sophistication of such forms”. Testing writing competency in terms of analyzing the syntactic complexity of students in writing compositions was initiated by Kellogg Hunt (1965) whose concept of minimal terminal units or „T‟ units is based on Chomsky‟s manifestation of the innate structure. Hunt terms this as a simple sentence. In his study, Hunt used the T-unit as the main measuring device to examine the syntacticdevelopment in the free writing of his subjects. The findings reveal that English-speaking children learn to use larger number of sentence-combining transformations per main clause in their writing. Hunt‟s concept was further used by O‟Donnell, Griffin and Norris (1967), Mellon, (1969),; O‟Hare, (1973); Combs, (1976); Daiker, et al. (1978); Morenberg,, et al. (1978), Faigley, (1979); Haswell, (1981); and Hudson, (2009). Hunt‟s study was also used as an impetus to analyse essays, poems and dialogues. Cynthia L. Hallen and Jennifer Shakespear (2002) adopted Kellogg Hunt‟s T-unit to analyse the poems of Emily Dickinson. The concept of T- unit has also been used as an important measure of testing writing proficiency in second language research (Arthur, 1979, Celce-Murcia and Santos, 1979; Perkins, 1980; Ferris and Politzer 1981; Foster & Tavakoli, 2009; Stockwell & Harrington, 2003; Ellis & Yuan, 2004; Beers & Nagy, 2009; Norrby 2007; Lu 2011; Haiyang Ai and Xiaofei Lu 2013; Wang and Slater, 2016.
automated computation of IPSyn. 4 CP is an exten- sively developed example of what can be achieved using only POS and morphological analysis. It does well on identifying items in IPSyn categories that do not require deeper syntactic analysis. However, the accuracy of overall scores is not high enough to be considered reliable in practical usage, in particu- lar for older children, whose utterances are longer and more sophisticated syntactically. In practice, researchers usually employ CP as a first pass, and manually correct the automatic output. Section 5 presents an evaluation of the CP version of IPSyn.
The specific hypothesis we address in this paper is whether a fully-data driven approach that uses only a few simple feature templates applied to syntactic dependency trees can capture the same information as the well-known Index of Productive Syntax, or IPSyn (Scarborough, 1990). In contrast to previous work that showed that the computation of IPSyn scores can be performed automatically by encoding each of the 60 language structures in a language-specific inventory (e.g. wh-questions with auxiliary inversion, propositional complements, conjoined sentences) as complex patterns over parse trees, we propose that child language development can instead be measured automatically in a way that is fully data-driven and can be applied to many languages for which accurate dependency parsers are available, without relying on carefully constructed lists of grammatical structures or complex syntactic patterns in each language. Specifically, we examine two hypotheses: (1) counts of features extracted from syntactic parse trees using only simple templates are at least as expressive of changes in language development as the Index of Productive Syntax (Scarborough, 1990), an empirically validated metric based on an inventory of grammatical structures derived from the child language literature; and (2) these parse tree features can be used to model language development without the use of an inventory of specific structures, assuming only the knowledge that in typically developing children the level of language development is correlated with age. We emphasize that the goal of this work is not to develop yet one more way to compute IPSyn scores automatically, but to show empirically that lists of grammatical structures such as those used to compute IPSyn are not essential to measure syntacticdevelopment in children.
It is very important for any theory which relies strongly on learning algorithms to show that it is indeed possible for children to learn to produce and control complex language very quickly, by using a simple learning procedure and without having to build a complex system of rules. If not, these theories would also have to provide the means to instantaneous acquisition of language structure, which would be quite difficult if not impossible. It has been shown above that it is possible to find a system that explains the initial language production of children without any innate language-specific features, which does not mean that the natural development of language will not induce properties such as language modularity and abstract syntactic competence later on. This system would be fully operative by the age of two and remain for some time the most basic and productive language mechanism. It might also remain active for adults because it is an efficient way of producing language when the cognitive load is heavy or speed is crucial (Peters, 1983, p. 80, pp. 105-106). However, the Three-Step Algorithm does not account for all language acquisition processes before the age of three. First, its rather crude mechanisms would produce many aberrant utterances on their own, if they were not regulated by other mechanisms. Second, some utterances clearly cannot be produced by the Three-Step Algorithm.
One of the potential drawbacks of our current approach is the need for a syntactic parsing pre- ceding the joint model. This previous parse is simply included to permit the extraction of syntax based features. These features (including the syn- tactic path) could be dynamically computed when performing the joint parsing in the cases in which the predicate coincides with the head of the modi- fier being processed. These cases account for only 63.6% of the training corpus arguments. If a pred- icate is located in a sibling sentence span, the dy- namic programming algorithm has not yet chosen which of the possible spans will be included in the final parse tree. Also, the predicate can be located at a lower level within the current span. These cases would require to recompute the score of the current span because syntactic path features are not available. The resulting cost would be pro- hibitive and approximate search needed. Our pre- vious parsing phase is just an efficient and simple solution to the feature extraction problem in the joint model.
He has also highlighted the role, played by NGOs to maintain the sustainable development position in accordance with changing scenario. Singh.S.Singh (2006) has also emphasized on formulating the models, before executing the development projects. The models play a significant role to managing the practical problematic areas of development and disaster management (Das S.K, Kumar Arun Kumar, 2009).Similarly, Rawat, M.S, Goswami, D.C, Vijay Bahuguna (2011) have insisted on formulating the ‘Sustainable Models’ so that a development strategy may be chalked out for the hilly region of Uttrakhand for sustainable development. On the other hand, Govt. of Himachal Pradesh has also identified the vulnerable areas of the state. EMP (Environmental Master Plan) recently prepared by the Department of Environment and Scientific Technology and approved by the vulnerable areas of the state, where future planning will have to done with utmost car e. The EMP has been adapted to main stream environment concerned into state’s development planning in sectors of economy for next 30 years. In this, there is need to mitigate the likely impact on rivers, flora and fauna and resulting change in lively hood because of multi-purpose river valley projects, power plants and industries. (Report on Infrastructure, Natural Resources Management and services, Department of Forest and Environment, Govt. of Himachal Pradesh, 2013)
Syntactic disorders among hearing-impaired children trained orally, have been reported over the last forty years. The implemented studies showed that the syntactic abilities of hearing-impaired children are different from that of normal-hearing children (5,6). In the field of the syntactic perception of object relative clauses, the performance of hearing-impaired children has been significantly reported to be lower than that of normal-hearing children (7-9). Davis and Blasdel examined the problem of hearing-impaired children on more complex constructions. They encountered children with perception task of sentences containing embedded relative clauses in the middle position. The analysis of their responses showed that the children chose a strategy of processing that focused on the final part of sentence. So when the children were shown four pictures and they were asked to refer any of these images which indicate the sentence: "The sheep that chased the man ate the grass", they often selected the picture in which a man was eating grass, despite the selected picture was meaningless and was not understandable. This implies that the children’s strategy in processing such a sentence was to interpret sentences containing all the embedded clauses in a middle position in terms of sequence of subject, verb and object. In this special study, hearing-impaired children almost, in 50% of cases, did not well understand the tense of complex sentences. Other syntactic structures in which hearing-impaired children had problems on their perception included: constructions of relativization, complementation, verb conjugation and pronominalization (10). Levitt, McGarr, and Geffner tested the syntactic abilities on a large number of hearing-impaired children. The results revealed a wide range of performance among children. This range included hearing-impaired children in normal and common conditions to hearing-impaired children in specific situations. One of the remarkable observations of this study was that the children who received early special education, had better language performance than children who had lacked such training (11).
The fact that structural priming does not rely on superficial comparisons between lexical items is now well-established. Nevertheless, it has been found that adults’ knowledge of a verb’s preferred argument structure (verb bias) influences their structure choice during priming tasks. Priming effects tend to be larger when prime and target sentences share a verb (the lexical boost; Pickering & Branigan, 1998), and the syntactic preference of both the target verb (target verb bias; Gries, 2005) and the prime verb (Bernolet & Hartsuiker, 2010; Jaeger & Snider, 2013) affect the size of the structural priming effect. For example, both Bernolet and Hartsuiker, and Jaeger and Snider have shown that priming is stronger when the prime verb’s bias does not match the prime structure in which it is presented, a phenomenon called prime surprisal. Taken together, these findings demonstrate that, although adults have abstract representations of syntactic structure, they also store links between verbs and the structures in which these verbs occur, and that these links can influence structural priming.
We are currently pursuing summaries for genes. Since iTerms have been shown in previous evalua- tions to represent important aspects of a gene’s func- tionality and behavior, we are investigating whether they are represented in gene summaries found in En- trezGene and UniProtKB. If so, an extractive sum- mary can be produced by choosing sentences for the gene and its iTerms. We are also considering de- veloping abstractive summaries. Our use of lexico- syntactic patterns can be extended to pick the exact relation between a gene and the iTerm. For exam- ple, by using the lexico-syntactic patterns, coupled with simplification, we can extract the following ex- act relations from the four sentences shown in Fig- ure 1: “Groucho is a corepressor”, “The wrpw motif recruits groucho”, “Groucho is implicated in notch signaling”, and “The eh1 repression domain binds groucho”. With these relations extracted, using text generation algorithms for textual realization and co- hesion, we can produce abstractive summaries.
art speech recognizer. For instance, Chen and Zechner (2011) reported a 50.5% word error rate (WER) and Yoon and Bhat (2012) reported a 30% WER in the recognition of ESL students’ spoken responses. These high error rates at the recogni- tion stage negatively affect the subsequent stages of the speech scoring system in general, and in particular, during a deep syntactic analysis, which operates on a long sequence of words as its con- text. As a result, measures of grammatical com- plexity that are closely tied to a correct syntac- tic analysis are rendered unreliable. Not surpris- ingly, Chen and Zechner (2011) studied measures of grammatical complexity via syntactic parsing and found that a Pearson’s correlation coefficient of 0.49 between syntactic complexity measures (derived from manual transcriptions) and profi- ciency scores, was drastically reduced to near non- existence when the measures were applied to ASR word hypotheses. This suggests that measures that rely on deep syntactic analysis are unreliable in current ASR-based scoring systems for sponta- neous speech.
Much has changed in recent years in the linguistic study of variation and change generally, but: ‘It’s sometimes claimed that there’s been no significant syntactic change in French since the end of the seventeenth century, and that the label Mod(ern)F(rench) reflects a three-century-long period of grammatical stability.’ (Rowlett 2007: 9)
The proposed parsing model is an extension of a classical arc-standard parser, integrating specific transitions for MWE detection. In order to deal with the two linguistic dimensions separately, it uses two stacks (instead of one). It is synchro- nized by using a single buffer, in order to handle the factorization of the two structures. It also in- cludes different hard constraints on the system in order to reduce ambiguities artificially created by the addition of new transitions. To the best of our knowledge, this system is the first transition-based parser that includes a specific mechanism for han- dling MWEs in two dimensions. Previous related research has usually proposed either pipeline ap- proaches with MWE identification performed ei- ther before or after dependency parsing (Kong et al., 2014; Vincze et al., 2013a) or workaround joint solutions using off-the-shelf parsers trained on dependency treebanks where MWEs are an- notated by specific subtrees (Nivre and Nilsson, 2004; Eryi˘git et al., 2011; Vincze et al., 2013b; Candito and Constant, 2014; Nasr et al., 2015). 2 Syntactic and Lexical Representations A standard dependency tree represents syntactic structure by establishing binary syntactic relations between words. This is an adequate representa-
Other methods restrict themselves to lexical and syntactic features. Ghosh et al. , Lin et al.  and Xu et al.  engineer a similar feature set to each other in their own approaches. Whilst Ghosh et al.  uses a features set composed of lexical fea- tures (surface expression and lemmata of tokens) and morpho-syntactic features (PoS, inflection, main verb of sentence, path from root to token in parse tree), Lin et al.  extends it by adding information about the neighbouring tokens. Xu et al.  enriches the set even more, considering the position of the token relative to the trigger (left or right), and its position in the sentence as a binary class (before the middle or after the middle of the sentence). Thus, they manage to reach 46% F-score in recognising both arguments when they employ automatic parses for feature extraction.
learning (MTL; Caruana, 1997) on several se- mantic and syntactic parsing tasks. We examine whether alternately optimizing two objectives, one for UCCA and one for SNACS, leads to mutually favorable biases via shared parameters. There are multiple ways the two tasks can be orchestrated: Independent MTL. This is the multitask learn- ing (MTL) setup from Hershcovich et al. (2018), where separate transition classifiers are trained on different tasks simultaneously, sharing and mutu- ally updating the BiLSTM encoding. 10 We con- sider as auxiliary tasks (a) SNACS scene role clas- sification and (b) the decision of which UCCA unit is refined by a SNACS-annotated token. We encode these tasks as parsing tasks analogous to UCCA parsing as follows: for each training item in (a), we create a graph consisting of a root and up to 4 children: the syntactic governor (if avail- able), the preposition token, the syntactic object (if available)—all of which have dummy edge labels— as well as a dummy terminal carrying the SNACS supersense. For each training item in (b), we con- sider the full UCCA structure, but the edge labels are simply boolean values indicating whether an edge is refined or not.
Pregroups are mathematical structures which were developed initially by Lambek and can be used to analyze sentences in English algebraically (Lambek, 1997). Pregroup calculus was a re- vision of Lambek’s previous categorial grammar called Syntactic Calculus (Lambek, 1958). Var- ious languages have since adopted the use of pregroup calculus as the formal representation of syntax of a fragment or a particular property of the language, including Arabic (Bargelli and Lambek, 2001b), French (Bargelli and Lambek, 2001a), German (Lambek, 2000), Japanese (Car- dinal, 2002), Persian (Sadrzadeh, 2007), Polish (Kislak-Malinowska, 2008), and Sanskrit (Casa- dio and Sadrzadeh, 2014), among others. Co- ecke et al. (2010)’s compositional distributional model of meaning also uses pregroup calculus as the compositional theory for grammatical types.
A few kernels based on dependency trees have also been proposed. Zelenko et al. (2003) pro- posed a tree kernel over shallow parse tree represen- tations of sentences. This tree kernel was slightly generalized by Culotta and Sorensen (2004) to com- pute similarity between two dependency trees. In addition to the words, this kernel also incorporates word classes into the kernel. The kernel is based on counting matching subsequences of children of matching nodes. But as was also noted in (Bunescu and Mooney, 2005a), this kernel is opaque i.e. it is not obvious what the implicit features are and the authors do not describe it either. In contrast, our dependency-based word subsequence kernel, which also computes similarity between two dependency trees, is very transparent with the implicit features being simply the dependency paths. Their kernel is also very time consuming and in their more general sparse setting it requires O(mn 3 ) time and O(mn 2 )
A developmental milestone is an ability that is achieved by most children by a certain age. Developmental milestones can involve physical, social, emotional, cognitive and communication skills such as walking, sharing with others, expressing emotions, recognizing familiar sounds and talking. All children develop in their own unique pace, as a direct result of both hereditary and environmental influences; there is a certain pattern of development that applies to nearly all children. Present study was undertaken in primary-schools of Hisar city of Haryana state to assess impact of intervention programme on developmental milestones of 6-10 years of group. Results of the study shows that after intervention programme significant differences were found in different developmental milestone i.e. language and physical. Thus it can be said that intervention having significant impact on developmental milestones.
The differences observed in our sample between the three groups, as well as the wide variability in perfor- mance of HIV infected children, suggest that a variety of mechanisms contribute to language risk or resilience, and that the impact of these mechanisms may be greater at older ages, or may act cumulatively over time . The potential pathways are multiple, although it requires a larger sample to investigate in detail the relative contri- bution of the sources of this variability in performance. First, vertical transmission may lead to subsequent HIV related damage to the central nervous system [24, 25]. Second, compromise to prenatal environment may lead to higher incidences of low-birth weight and prematu- rity factors [26, 27] which have been associated with poor developmental outcomes. Third, compromise of the post- natal home environment may act by limiting stimulation through suboptimal parenting behavior . Specific mechanisms for this last pathway might include exposure to stressors such as poor maternal mental health, mater- nal chronic illness, or constrained economic circum- stances leading to restricted resources such as fewer toys and less opportunity for stimulation .
While opportunities may, therefore, abound for school-based subject knowledge development in principle, there exists a potential inherent problem. As pointed out by Mutton, Burn & Hagger (2010), schools are not only sites for student teacher learning but also for their demonstration of practical competence. The socialising influence of the school’s community is considerable and so newcomers need help to identify learning possibilities that go beyond mere experience. This is a sentiment echoed by Ellis (2010) who rails against an ‘impoverished’ view of experience as the transfer of expertise from mentor to student. Instead, he argues for a participatory model based around collaborative inquiry into practice. A further factor for consideration is the role of the university in this enterprise. Furlong (2013) draws attention to the marginalisation of the university in many forms of teacher education but suggests that two important roles remain: helping teachers to develop practical theories and exposing them to wider principles or perspectives beyond their immediate experience. The second of these resonates with Young’s (2013) notion of powerful knowledge and implies that the university may provide an important means of reconciling the situated with the generalizable.