• Title/Summary/Keyword: Korean Language Sentence Patterns

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Native Influence on the Production of English Intonation

  • Kim, Ok-Young
    • Speech Sciences
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    • v.15 no.1
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    • pp.25-36
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    • 2008
  • Language transfer means that the speaker's first language or previously acquired language influences on the production of the target language. This study aims at examining if there is native language influence on the production of English intonation by Korean speakers. The pitch accent patterns and the values of duration, F0, and intensity of the stressed vowel of the word with emphatic accent in the sentence produced by Korean speakers are compared to those of American English speakers. The results show that when the word receives emphatic accent in the sentence, American English speakers put H* accent on the stressed syllable of the word, but Korean speakers mostly assign high pitch on the last syllable of the word and have LH tonal pattern despite the fact that primary stress does not come on the last syllable within a word. In addition, comparison of the values of duration, F0, and intensity of the stressed vowel of the word with emphatic accent to those of the word with unmarked neutral accent shows that Korean speakers do not realize the intonation of the accented word appropriately because the values decrease even though the word has emphatic accent. This study finds out that there are differences in the production of English intonation of the word with emphatic accent between native speakers of English and Korean speakers, and that there is negative transfer of Korean intonation pattern to the production of English intonation by Korean speakers.

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The Effects of Increased Processing Demands on the Sentence Comprehension of Korean-speaking Adults with Aphasia (지연된 자극 제시가 실어증 환자의 문장 이해에 미치는 영향: 반응정확도와 반응시간을 중심으로)

  • Choi, So-Young
    • Phonetics and Speech Sciences
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    • v.4 no.2
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    • pp.127-134
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    • 2012
  • The purpose of this study is to present evidence for a particular processing approach based on the language-specific characteristics of Korean. To compare individuals' sentence-comprehension abilities, this study measured the accuracy and reaction times (RT) of 12 aphasic patients (AP) and 12 normal controls (NC) during a sentence-picture matching task. Four versions of a sentence were constructed with the two types of voice (active/passive) and two types of word order (agent-first/patient-first). To examine the effects of increased processing demand, picture stimuli were manipulated in such a way that they appeared immediately after the sentence was presented. As expected, the AP group showed higher error rates and longer RT for all conditions than the NC group. Furthermore, Korean speakers with aphasia performed above a chance level in sentence comprehension, even with passive sentences. Aphasics understood sentences more quickly and accurately when they were given in the active voice and with agent-first order. The patterns of the NC group were similar. These results confirm that Korean adults with aphasia do not completely lose their knowledge of sentence comprehension. When the processing demand was increased by delaying the picture stimulus onset, the effect of increased processing demands on RT was more pronounced in the AP than in the NC group. These findings fit well with the idea that the computational system for interpreting sentences is intact in aphasics, but its ability is compromised when processing demands increase.

Pronoun Resolution in French Discourse by Korean-learners of French (한국인 프랑스어 학습자의 프랑스어 담화 이해와 대명사 해석 연구)

  • Ahn, Eui-Jeen;Song, Hyun-Joo;Kim, Min-Ju;Leem, Jai-Ho
    • Korean Journal of Cognitive Science
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    • v.25 no.4
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    • pp.417-433
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    • 2014
  • This research examined whether Korean-learners of French were sensitive to discourse structure in anaphoric pronoun resolution. In the experiments, participants read three-sentenced stories and made judgements about how the last sentence of each story makes sense in relation to previous two sentences on a 7-point Likert scale. The stories differed in whether the subject of the last sentence continued the subject of the preceding sentence, and whether the subject of the last sentence was mentioned with a pronoun or a proper noun. The results from French participants replicated the patterns shown in previous studies. In contrast, Koreans exhibited greater difficulty in interpreting pronoun-subject sentences than noun-subject sentences regardless of subject continuity. These findings are discussed within the context of developmental perspective, which suggests the processing of co-referential interpretation may interact with language proficiency.

Hypernetwork-based Natural Language Sentence Generation by Word Relation Pattern Learning (단어 간 관계 패턴 학습을 통한 하이퍼네트워크 기반 자연 언어 문장 생성)

  • Seok, Ho-Sik;Bootkrajang, Jakramate;Zhang, Byoung-Tak
    • Journal of KIISE:Software and Applications
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    • v.37 no.3
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    • pp.205-213
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    • 2010
  • We introduce a natural language sentence generation (NLG) method based on learning of word-association patterns. Existing NLG methods assume the inherent grammar rules or use template based method. Contrary to the existing NLG methods, the presented method learns the words-association patterns using only the co-occurrence of words without additional information such as tagging. We employ the hypernetwork method to analyze and represent the words-association patterns. As training going on, the model complexity is increased. After completing each training phase, natural language sentences are generated using the learned hyperedges. The number of grammatically plausible sentences increases after each training phase. We confirm that the proposed method has a potential for learning grammatical properties of training corpuses by comparing the diversity of grammatical rules of training corpuses and the generated sentences.

Prosody in Spoken Language Processing

  • Schafer Amy J.;Jun Sun-Ah
    • Proceedings of the Acoustical Society of Korea Conference
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    • spring
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    • pp.7-10
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    • 2000
  • Studies of prosody and sentence processing have demonstrated that prosodic phrasing can exhibit strong effects on processing decisions in English. In this paper, we tested Korean sentence fragments containing syntactically ambiguous Adj-N1-N2 strings in a cross-modal naming task. Four accentual phrasing patterns were tested: (a) the default phrasing pattern, in which each word forms an accentual phrase; (b) a phrasing biased toward N1 modification; (c) a phrasing biased toward complex-NP modification; and (d) a phrasing used with adjective focus. Patterns (b) and (c) are disambiguating phrasings; the other two are commonly found with both interpretations and are thus ambiguous. The results showed that the naming time of items produced in the prosody contradicting the semantic grouping is significantly longer than that produced in either default or supporting prosody, We claim that, as in English, prosodic information in Korean is parsed into a well-formed prosodic representation during the early stages of processing. The partially constructed prosodic representation produces incremental effects on syntactic and semantic processing decisions and is retained in memory to influence reanalysis decisions.

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Prosodic Annotation in a Thai Text-to-speech System

  • Potisuk, Siripong
    • Proceedings of the Korean Society for Language and Information Conference
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    • 2007.11a
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    • pp.405-414
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    • 2007
  • This paper describes a preliminary work on prosody modeling aspect of a text-to-speech system for Thai. Specifically, the model is designed to predict symbolic markers from text (i.e., prosodic phrase boundaries, accent, and intonation boundaries), and then using these markers to generate pitch, intensity, and durational patterns for the synthesis module of the system. In this paper, a novel method for annotating the prosodic structure of Thai sentences based on dependency representation of syntax is presented. The goal of the annotation process is to predict from text the rhythm of the input sentence when spoken according to its intended meaning. The encoding of the prosodic structure is established by minimizing speech disrhythmy while maintaining the congruency with syntax. That is, each word in the sentence is assigned a prosodic feature called strength dynamic which is based on the dependency representation of syntax. The strength dynamics assigned are then used to obtain rhythmic groupings in terms of a phonological unit called foot. Finally, the foot structure is used to predict the durational pattern of the input sentence. The aforementioned process has been tested on a set of ambiguous sentences, which represents various structural ambiguities involving five types of compounds in Thai.

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Sentence design for speech recognition database

  • Zu Yiqing
    • Proceedings of the KSPS conference
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    • 1996.10a
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    • pp.472-472
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    • 1996
  • The material of database for speech recognition should include phonetic phenomena as much as possible. At the same time, such material should be phonetically compact with low redundancy[1, 2]. The phonetic phenomena in continuous speech is the key problem in speech recognition. This paper describes the processing of a set of sentences collected from the database of 1993 and 1994 "People's Daily"(Chinese newspaper) which consist of news, politics, economics, arts, sports etc.. In those sentences, both phonetic phenometla and sentence patterns are included. In continuous speech, phonemes always appear in the form of allophones which result in the co-articulary effects. The task of designing a speech database should be concerned with both intra-syllabic and inter-syllabic allophone structures. In our experiments, there are 404 syllables, 415 inter-syllabic diphones, 3050 merged inter-syllabic triphones and 2161 merged final-initial structures in read speech. Statistics on the database from "People's Daily" gives and evaluation to all of the possible phonetic structures. In this sentence set, we first consider the phonetic balances among syllables, inter-syllabic diphones, inter-syllabic triphones and semi-syllables with their junctures. The syllabic balances ensure the intra-syllabic phenomena such as phonemes, initial/final and consonant/vowel. the rest describes the inter-syllabic jucture. The 1560 sentences consist of 96% syllables without tones(the absent syllables are only used in spoken language), 100% inter-syllabic diphones, 67% inter-syllabic triphones(87% of which appears in Peoples' Daily). There are rougWy 17 kinds of sentence patterns which appear in our sentence set. By taking the transitions between syllables into account, the Chinese speech recognition systems have gotten significantly high recognition rates[3, 4]. The following figure shows the process of collecting sentences. [people's Daily Database] -> [segmentation of sentences] -> [segmentation of word group] -> [translate the text in to Pin Yin] -> [statistic phonetic phenomena & select useful paragraph] -> [modify the selected sentences by hand] -> [phonetic compact sentence set]

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Prosodic Contour Generation for Korean Text-To-Speech System Using Artificial Neural Networks

  • Lim, Un-Cheon
    • The Journal of the Acoustical Society of Korea
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    • v.28 no.2E
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    • pp.43-50
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    • 2009
  • To get more natural synthetic speech generated by a Korean TTS (Text-To-Speech) system, we have to know all the possible prosodic rules in Korean spoken language. We should find out these rules from linguistic, phonetic information or from real speech. In general, all of these rules should be integrated into a prosody-generation algorithm in a TTS system. But this algorithm cannot cover up all the possible prosodic rules in a language and it is not perfect, so the naturalness of synthesized speech cannot be as good as we expect. ANNs (Artificial Neural Networks) can be trained to learn the prosodic rules in Korean spoken language. To train and test ANNs, we need to prepare the prosodic patterns of all the phonemic segments in a prosodic corpus. A prosodic corpus will include meaningful sentences to represent all the possible prosodic rules. Sentences in the corpus were made by picking up a series of words from the list of PB (phonetically Balanced) isolated words. These sentences in the corpus were read by speakers, recorded, and collected as a speech database. By analyzing recorded real speech, we can extract prosodic pattern about each phoneme, and assign them as target and test patterns for ANNs. ANNs can learn the prosody from natural speech and generate prosodic patterns of the central phonemic segment in phoneme strings as output response of ANNs when phoneme strings of a sentence are given to ANNs as input stimuli.

A Comparative Study on Korean Connective Morpheme '-myenseo' to the Chinese expression - based on Korean-Chinese parallel corpus (한국어 연결어미 '-면서'와 중국어 대응표현의 대조연구 -한·중 병렬 말뭉치를 기반으로)

  • YI, CHAO
    • Cross-Cultural Studies
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    • v.37
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    • pp.309-334
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    • 2014
  • This study is based on the Korean-Chinese parallel corpus, utilizing the Korean connective morpheme '-myenseo' and contrasting with the Chinese expression. Korean learners often struggle with the use of Korean Connective Morpheme especially when there is a lexical gap between their mother language. '-myenseo' is of the most use Korean Connective Morpheme, it usually contrast to the Chinese coordinating conjunction. But according to the corpus, the contrastive Chinese expression to '-myenseo' is more than coordinating conjunction. So through this study, can help the Chinese Korean language learners learn easier while studying '-myenseo', because the variety Chinese expression are found from the parallel corpus that related to '-myenseo'. In this study, firstly discussed the semantic features and syntactic characteristics of '-myenseo'. The significant semantic features of '-myenseo' are 'simultaneous' and 'conflict'. So in this chapter the study use examples of usage to analyse the specific usage of '-myenseo'. And then this study analyse syntactic characteristics of '-myenseo' through the subject constraint, predicate constraints, temporal constraints, mood constraints, negatives constraints. then summarize them into a table. And the most important part of this study is Chapter 4. In this chapter, it contrasted the Korean connective morpheme '-myenseo' to the Chinese expression by analysing the Korean-Chinese parallel corpus. As a result of the analysis, the frequency of the Chinese expression that contrasted to '-myenseo' is summarized into

    . It can see from the table that the most common Chinese expression comparative to '-myenseo' is non-marker patterns. That means the connection of sentence in Korean can use connective morpheme what is a clarifying linguistic marker, but in Chinese it often connect the sentence by their intrinsic logical relationships. So the conclusion of this chapter is that '-myenseo' can be comparative to Chinese conjunction, expression, non-marker patterns and liberal translation patterns, which are more than Chinese conjunction that discovered before. In the last Chapter, as the conclusion part of this study, it summarized and suggest the limitations and the future research direction.

  • Predicate Recognition Method using BiLSTM Model and Morpheme Features (BiLSTM 모델과 형태소 자질을 이용한 서술어 인식 방법)

    • Nam, Chung-Hyeon;Jang, Kyung-Sik
      • Journal of the Korea Institute of Information and Communication Engineering
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      • v.26 no.1
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      • pp.24-29
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      • 2022
    • Semantic role labeling task used in various natural language processing fields, such as information extraction and question answering systems, is the task of identifying the arugments for a given sentence and predicate. Predicate used as semantic role labeling input are extracted using lexical analysis results such as POS-tagging, but the problem is that predicate can't extract all linguistic patterns because predicate in korean language has various patterns, depending on the meaning of sentence. In this paper, we propose a korean predicate recognition method using neural network model with pre-trained embedding models and lexical features. The experiments compare the performance on the hyper parameters of models and with or without the use of embedding models and lexical features. As a result, we confirm that the performance of the proposed neural network model was 92.63%.