• Speech Sciences
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• v.14 no.1
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• pp.21-35
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• 2007

This paper attempts to investigate phonetic substances of the stress patterns of English compounds and noun phrases, showing that the theoretically derived stress structures are not consistent with the accentual patterns in real utterances. Even though it has been long claimed that compounds have the stress pattern [1 3] and that noun phrases, [2 1] as in Chomsky & Halle (1968), their difference has not been yet explored empirically or phonetically. I present a phonetic experiment conducted to see if there is any difference along the tonal contours, mostly focusing on their pitch accent distribution. 36 different compounds and 36 different noun phrases included in carrier sentences were examined, and they were varied in position within a sentence. Results showed that various accentual patterns were produced, and among them, [H* X] predominantly occurs in all three positions in both compounds and noun phrases, whereas the patterns [X H*] and [X X] appear relatively more frequently in final position than in initial and medial position. Furthermore, the pattern [Ac + No], in which the preceding element is pitch-accented with no accent on the following one, is the major stress pattern in both compounds and noun phrases and in all three sentence positions. This suggests that there seems to be no difference in accentual patterns between compounds and noun phrases, which is not consistent with the hypothesis. The results are interpreted as saying that the preceding element alone tends to be prominent with no accent following it both in compounds and noun phrases, and that therefore, theoretically speculated phonological claims are not always phonetically supported.

• Speech Sciences
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• v.12 no.4
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• pp.153-166
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• 2005

This paper attempts to examine the accent implementation and perception of noun phrases and compound nouns in English sentences, arguing that primary stress of noun phrase and compound noun is realized in relative prominence in intonation. The production test examines how the stress patterns of the noun phrases and compound nouns are realized in intonation of the English native speakers' utterances. The perception test investigates English and Korean listeners' comprehension of the intonation of the noun phrases and compound nouns. And the results of this experimental study show that speakers and listeners produce and perceive the primary stress as a relatively prominent accent even if in contrast of English listeners, Korean learners have difficulty in using the cue of pitch accent location and figuring out compound nouns and noun phrases.

• Speech Sciences
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• v.11 no.3
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• pp.95-109
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• 2004

Metrical Phonology has asserted that stress shift does not occur in English compounds because it violates the Continuous Column Constraint. Noun phrases, on the other hand, freely allow for stress shift, whereby the preceding stress moves forward to the preceding heavy syllable. This paper hypothesizes that stress does not shift in compounds as opposed to noun phrases and compares their pitch accentual patterns in a phonetic experiment. More specifically, we examined two-word combinations, noun phrases and compounds, whose boundaries involve stress clash and assured that the preceding words involve a heavy syllable ahead of the stress to guarantee the place for a shifting stress. Depending on where the preceding pitch accent is aligned, stress shift is determined. Results show that stress shift occurs in approximately 47% of the noun phrases and 59% of the compounds; therefore, the hypothesis is not borne out. This suggests that the surface representations derived by phonological rules may not be implemented in real utterance but that phonetic forms may be determined by the phonetic constraints. directly operating on human speech.

• Journal of Korea Multimedia Society
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• v.20 no.3
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• pp.533-542
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• 2017

Novels include various character names, depending on the genre and the spatio-temporal background of the novels and the nationality of characters. Besides, characters and their names in a novel are created by the author's pen and imagination. As a result, any proper noun dictionary cannot include all kinds of character names. In addition, the novels translated into Korean have character names consisting of two or more nouns (such as "Harry Potter"). In this paper, we propose a method to extract noun phrases for character names and to cluster the noun phrases into coreferents for the same character name. In the extraction of noun phrases, we utilize KKMA morpheme analyzer and CPFoAN character identification tool. In clustering the noun phrases into coreferents, we construct a directed graph with the character names extracted by CPFoAN and the extracted noun phrases, and then we create name sets for characters by traversing connected subgraphs in the directed graph. With four novels translated into Korean, we conduct a survey to evaluate the proposed method. The results show that the proposed method will be useful for speaker identification as well as for constructing the social network of characters.

• Proceedings of the Korean Society for Emotion and Sensibility Conference
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• 2008.10a
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• pp.90-93
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• 2008

In natural language, it is common that repetitive constituents in an expression are to be left out and it is necessary to figure out the constituents omitted at analyzing the meaning of the sentence. This paper is on recognition of boundaries of parallel noun phrases by figuring out constituents omitted. Recognition of parallel noun phrases can greatly reduce complexity at the phase of sentence parsing. Moreover, in natural language information retrieval, recognition of noun with modifiers can play an important role in making indexes. We propose an unsupervised probabilistic model that identifies parallel cores as well as boundaries of parallel noun phrases conjoined by a conjunctive particle. It is based on the idea of swapping constituents, utilizing symmetry (two or more identical constituents are repeated) and reversibility (the order of constituents is changeable) in parallel structure. Semantic features of the modifiers around parallel noun phrase, are also used the probabilistic swapping model. The model is language-independent and in this paper presented on parallel noun phrases in Korean language. Experiment shows that our probabilistic model outperforms symmetry-based model and supervised machine learning based approaches.

• Speech Sciences
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• v.9 no.2
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• pp.109-132
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• 2002

The purpose of this study is to examine the focus realization of [Adjective+Noun] phrases which are used in English classroom situations. In order to examine this, two production and one perception experiments were designed. The noun phrases in the first two production experiments are divided into three patterns according to the location of focus. The difference between the two production experiments is that in the first experiment the focused words are contextually given in the classroom situation, but in the second experiment they are presented in written form. We compare the native English teachers' focus realization of noun phrases with that of Korean teachers from the point of view of intonational phonology. In the perception test, we examine how the uttered sentences are perceived by English native speakers and Korean native speakers. The results from the three experiments show that native English teachers' focus realization is quite consistent with informational structure. Also, there is a significant difference in pitch range of adjectives and nouns when the native speakers give pitch accents on the two content words, and the uttered sentences are mostly perceived as well as the speakers' intentions. As for Korean speakers, however, they usually focus only on the adjective or they focus on both the adjective and the noun, regardless of the relative informativeness of these words. From these findings, we can conclude that focus realization of Korean teachers is rather inconsistent with respect to informational structure when compared to that of native English teachers.

• Asia Pacific Journal of Corpus Research
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• v.4 no.1
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• pp.1-23
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• 2023

The Japanese language, as a typical agglutinating language, permits large noun phrases (NP) containing ten or more morphemes. In this paper, we argue that the nature of the NP in Japanese is changing. Our data are drawn from the Balanced Corpus of Contemporary Written Japanese. We conduct a series of apparent-time studies of ongoing changes in complex NPs. We first examine the length of compound nouns, followed by the usage of bound suffixes. We then examine ongoing changes in complex NPs that contain genitive case markers. Finally, we examine noun incorporation. All of our studies show a trend towards shorter, less complex NPs. Furthermore, our results suggest that the usage rate of phrases that modify the noun inside the NP (compound nouns, bound nouns, NPs containing genitive case, noun incorporation) appears to be decreasing over time. On the other hand, the usage rate of modifying material outside of the NP (positional phrases, relative clauses) appears to be increasing over time. We conclude by suggesting that our results reflect a diachronic change of decreasing synthetic morphology and increasing analytic morphology. We end by pointing out the implications of this work on our understanding syntheticity and analyticity.

• Journal of Intelligence and Information Systems
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• v.21 no.2
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• pp.131-150
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• 2015

Omission of noun phrases for obligatory cases is a common phenomenon in sentences of Korean and Japanese, which is not observed in English. When an argument of a predicate can be filled with a noun phrase co-referential with the title, the argument is more easily omitted in Encyclopedia texts. The omitted noun phrase is called a zero anaphor or zero pronoun. Encyclopedias like Wikipedia are major source for information extraction by intelligent application systems such as information retrieval and question answering systems. However, omission of noun phrases makes the quality of information extraction poor. This paper deals with the problem of developing a system that can restore omitted noun phrases in encyclopedia documents. The problem that our system deals with is almost similar to zero anaphora resolution which is one of the important problems in natural language processing. A noun phrase existing in the text that can be used for restoration is called an antecedent. An antecedent must be co-referential with the zero anaphor. While the candidates for the antecedent are only noun phrases in the same text in case of zero anaphora resolution, the title is also a candidate in our problem. In our system, the first stage is in charge of detecting the zero anaphor. In the second stage, antecedent search is carried out by considering the candidates. If antecedent search fails, an attempt made, in the third stage, to use the title as the antecedent. The main characteristic of our system is to make use of a structural SVM for finding the antecedent. The noun phrases in the text that appear before the position of zero anaphor comprise the search space. The main technique used in the methods proposed in previous research works is to perform binary classification for all the noun phrases in the search space. The noun phrase classified to be an antecedent with highest confidence is selected as the antecedent. However, we propose in this paper that antecedent search is viewed as the problem of assigning the antecedent indicator labels to a sequence of noun phrases. In other words, sequence labeling is employed in antecedent search in the text. We are the first to suggest this idea. To perform sequence labeling, we suggest to use a structural SVM which receives a sequence of noun phrases as input and returns the sequence of labels as output. An output label takes one of two values: one indicating that the corresponding noun phrase is the antecedent and the other indicating that it is not. The structural SVM we used is based on the modified Pegasos algorithm which exploits a subgradient descent methodology used for optimization problems. To train and test our system we selected a set of Wikipedia texts and constructed the annotated corpus in which gold-standard answers are provided such as zero anaphors and their possible antecedents. Training examples are prepared using the annotated corpus and used to train the SVMs and test the system. For zero anaphor detection, sentences are parsed by a syntactic analyzer and subject or object cases omitted are identified. Thus performance of our system is dependent on that of the syntactic analyzer, which is a limitation of our system. When an antecedent is not found in the text, our system tries to use the title to restore the zero anaphor. This is based on binary classification using the regular SVM. The experiment showed that our system's performance is F1 = 68.58%. This means that state-of-the-art system can be developed with our technique. It is expected that future work that enables the system to utilize semantic information can lead to a significant performance improvement.

• Journal of KIISE:Software and Applications
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• v.36 no.4
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• pp.320-328
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• 2009

In general, there are two types of noun phrases(NP): Base Noun Phrase(BNP), and Maximal-Length Noun Phrase(MNP). MNP identification can largely reduce the complexity of full parsing, help analyze the general structure of complex sentences, and provide important clues for detecting main predicates in Chinese sentences. In this paper, we propose a 2-phase hybrid approach for MNP identification which adopts salient features such as expanded chunks and classified punctuations to improve performance. Experimental result shows a high quality performance of 89.66% in $F_1$-measure.

• Journal of the Korea Society of Computer and Information
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• v.22 no.3
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• pp.107-113
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• 2017

Most of online bookstores are providing a user with the bibliographic book information rather than the concrete information such as thematic words and atmosphere. Especially, thematic words help a user to understand books and cast a wide net. In this paper, we propose an efficient extraction method of thematic words from book text by applying the compound noun and noun phrase synthetic method. The compound nouns represent the characteristics of a book in more detail than single nouns. The proposed method extracts the thematic word from book text by recognizing two types of noun phrases, such as a single noun and a compound noun combined with single nouns. The recognized single nouns, compound nouns, and noun phrases are calculated through TF-IDF weights and extracted as main words. In addition, this paper suggests a method to calculate the frequency of subject, object, and other roles separately, not just the sum of the frequencies of all nouns in the TF-IDF calculation method. Experiments is carried out in the field of economic management, and thematic word extraction verification is conducted through survey and book search. Thus, 9 out of the 10 experimental results used in this study indicate that the thematic word extracted by the proposed method is more effective in understanding the content. Also, it is confirmed that the thematic word extracted by the proposed method has a better book search result.