• Phonetics and Speech Sciences
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• v.14 no.2
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• pp.1-10
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• 2022

A wh-phrase positioned in an embedded clause can be interpreted as having a matrix scope if the sentence is produced with proper prosodic structures such as the wh-intonation. In a previous experiment, a sentence with a wh-phrase in an embedded clause was given to 40 speakers of Gyeongsang Korean. A script containing the sentence was provided to induce a matrix scope interpretation for the wh-phrase. These 40 utterances were prepared as stimuli for a perception test to verify whether the wh-phrases in the stimuli were perceived as having matrix scopes. Each utterance was played thrice to 24 subjects. The results showed that more than half of the 72 responses indicated a preference for an embedded scope rather than a matrix scope in 20 of the utterances. A multiple linear regression analysis showed that the matrix scope responses were best predicted by the magnitude of the pitch prominence in a prosodic word consisting of an embedded verb and a complementizer. The pitch prominence was calculated by subtracting the fundamental frequency (F0) at the right edge of the prosodic word from the peak F0 in the same prosodic word. The smaller the magnitude, the more matrix responses there were. These results suggest that the categorical perception of wh-scopes is based on the magnitude of pitch prominence.

• Phonetics and Speech Sciences
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• v.14 no.4
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• pp.1-10
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• 2022

The Korean polysemic ending '-(eu)lgeol' can has two different meanings, 'guess' and 'regret'. These are expressed by different boundary-tone types: a rising tone for guess, a falling one for regret. Therefore the sentence-final boundary-tone type is the most salient prosodic feature. However, besides tone type, the pitch difference between the final and penultimate syllables of '-(eu)lgeol' can also affect semantic discrimination. To investigate this aspect, we conducted a perception test using two sentences that were morphologically and syntactically identical. These two sentences were spoken using different boundary-tone types by a Korean native speaker. From these two sentences, the experimental stimuli were generated by artificially raising or lowering the pitch of the boundary syllable by 1Qt while fixing the pitch of the penultimate syllable and boundary-tone type. Thirty Korean native speakers participated in three levels of perceptual test, in which they were asked to mark whether the experimental sentences they listened to were perceived as guess or regret. The results revealed that regardless of boundary-tone types, the larger the pitch difference between the final and penultimate syllable in the positive direction, the more likely it is perceived as guess, and the smaller the pitch difference in the negative direction, the more likely it is perceived as regret.

• Journal of Information Technology Services
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• v.16 no.4
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• pp.149-160
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• 2017

Sentiment analysis is the process of determining whether a piece of document, text or conversation is positive, negative, neural or other emotion. Sentiment analysis has been applied for several real-world applications, such as chatbot. In the last five years, the practical use of the chatbot has been prevailing in many field of industry. In the chatbot applications, to recognize the user emotion, sentiment analysis must be performed in advance in order to understand the intent of speakers. The specific emotion is more than describing positive or negative sentences. In light of this context, we propose deep learning models for conducting multi-class sentiment analysis for identifying speaker's emotion which is categorized to be joy, fear, guilt, sad, shame, disgust, and anger. Thus, we develop convolutional neural network (CNN), long short term memory (LSTM), and multi-layer neural network models, as deep neural networks models, for detecting emotion in a sentence. In addition, word embedding process was also applied in our research. In our experiments, we have found that long short term memory (LSTM) model performs best compared to convolutional neural networks and multi-layer neural networks. Moreover, we also show the practical applicability of the deep learning models to the sentiment analysis for chatbot.

• International Journal of Advanced Culture Technology
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• v.7 no.4
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• pp.246-254
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• 2019

The purpose of this study is to analyze the issues related to urban regeneration project at the present time through surveys and interviews of participants in the urban regeneration leading project of Suncheon city. Most of the comments were related to business fragmentation and things that should be improved in the future. The text network technique is applied to the subject analysis using unstructured text data. As a result of the frequency of appearance and analysis of page rank centrality between words, words of 'parking', 'need', 'lack', 'region' and 'resident' appeared at the top, and the result of analyzing the mediation centrality of key words showed 'culture', 'Need', 'region', 'inflow' and 'lack' appeared at the top. In the network analysis, the most central words appeared, and many words appeared in the important position in the sentence. Text network analysis has provided timely results in terms of sustainability after completion of the Suncheon City Regeneration Leading Project..

• Korean Journal of English Language and Linguistics
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• v.4 no.2
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• pp.117-149
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• 2004

The paper is to argue against the asymmetric CP-V2 analysis of Old English, according to which finite verbs invariably undergo movement into a clause-final T within subordinate clauses and reach the functional head C within main clauses. The asymmetric CP-V2 analysis, first of all, faces difficulty in explaining a wide range of post-verbal elements within subordinate clauses. To resolve the problem, the analysis has to abandon the obligatoriness of V-to-T movement or introduce various types of extraposition whose status is dubious as a legitimate syntactic operation. Obligatory V-to-T movement in Old English lacks conceptual justification as well. Crosslinguistic evidence reveals that morphological richness in verbal inflection cannot entail overt verb movement. Moreover, the operation is always string-vacuous under the asymmetric CP- V2 analysis and has no effect at the interfaces, in violation of the principle of economy. The distribution of Old English finite verbs in main clauses also undermines the asymmetric CP-V2 analysis. Conceptually speaking, a proper syntactic trigger cannot be confirmed to motivate obligatory verb movement to C. The operation not only gets little support from nominative Case marking, the distribution of expletives, or complementizer agreement but also requires the unconvincing stipulation that expletives as well as sentence-initial subjects result from string-vacuous topicalization. Finally, textual evidence testifies that Old English sometimes permits non-V2 ordering patterns, many of which remain unexplained under the asymmetric CP-V2 analysis.

• Journal of the Institute of Electronics and Information Engineers
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• v.51 no.8
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• pp.66-74
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• 2014

Recently a variety of study of Korean parsing system is carried out by many software engineers and linguists. The parsing system mainly uses the method of machine learning or symbol processing paradigm. But the parsing system using machine learning has long training time because the data of Korean sentence is very big. And the system shows the limited recognition rate because the data has self error. In this thesis we design system using feature module which can reduce training time and analyze the recognized rate each the number of training sentences and repetition times. The designed system uses the separated modules and sorted table for binary search. We use the refined 36,090 sentences which is extracted by Sejong Corpus. The training time is decreased about three hours and the comparison of recognized rate is the highest as 84.54% when 10,000 sentences is trained 50 times. When all training sentence(32,481) is trained 10 times, the recognition rate is 82.99%. As a result it is more efficient that the system is used the refined data and is repeated the training until it became the steady state.

• Phonetics and Speech Sciences
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• v.5 no.1
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• pp.81-90
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• 2013

During adolescence the mutational period is characterized by the changes in the laryngeal structure, the length of the vocal cords, and a tone of voice. Usually, adolescents at 15 or 16 reach the voice of adults but the mutational period is sometimes delayed. Therefore, studies on the voice of adolescents between 16 ~ 18 right after the mutational period are required. Accordingly, this paper attempted to provide basic data about the normal standard for patients with voice disorders during this period by evaluating the vocal characteristics of males and females between 16 ~ 18 with an objective device bycomparing and analyzing them by sex and age. The study was conducted on a total of 60 subjects composed of each 10 subjects of each age. The vocal analysis was conducted by MPT (Maximum Phonation Time) measurement, sustained vowels and sentence reading. As for /a/ sustained vowels, fundamental frequency, hereinafter referred to as $F_0$, jitter, shimmer, noise-to-harmonic ratio, hereinafter referred to as NHR were measured by using the Multi-dimensional voice program (MDVP) among the Multi-Speech program of Computerized Speech Lab (Kay Elemetrics). The sentence reading, mean $F_0$, maximum $F_0$ and minimum $F_0$ were measured using the Real-Time Pitch (RTP) Model 5121 among the Multi-Speech program of Computerized Speech Lab (Kay Elemetrics). As a result, according to sex, there were statistically significant differences in $F_0$, jitter, shimmer, mean $F_0$, maximum $F_0$, and minimum $F_0$; and according to age, there were statistically significant differences in MPT. In conclusion, the voice of the adolescents between 16 ~ 18 reached the maturity levels of adults but the voice quality which can be considered on the scale of voice disorders showed transition to the voice of an adult during the mutational period.

• The Transactions of the Korea Information Processing Society
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• v.6 no.1
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• pp.247-252
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• 1999

In order to realize a speech coding at low bit rates, a pitch information is useful parameter. In case of extracting an average pitch information form continuous speech, the several pitch errors appear in a frame which consonant and vowel are coexistent; in the boundary between adjoining frames and beginning or ending of a sentence. In this paper, I propose an Individual Pitch (IP) extraction method using residual signals of the FIR-STREAK digital filter in order to restrict the pitch extraction errors. This method is based on not averaging pitch intervals in order to accomodate the changes in each pitch interval. As a result, in case of Ip extraction method suing FIR-STREAK digital filter, I can't find the pitch errors in a frame which consonant and vowel are consistent; in the boundary between adjoining frames and beginning or ending of a sentence. This method has the capability of being applied to many fields, such as speech coding, speech analysis, speech synthesis and speech recognition.

• The KIPS Transactions:PartB
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• v.18B no.5
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• pp.325-332
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• 2011

Social Network Services(SNS) such as Twitter, Facebook and Myspace have gained popularity worldwide. Especially, sentiment analysis of SNS users' sentence is very important since it is very useful in the opinion mining. In this paper, we propose a new sentiment classification method of sentences which contains formal and informal vocabulary such as emoticons, and newly coined words. Previous methods used only formal vocabulary to classify sentiments of sentences. However, these methods are not quite effective because internet users use sentences that contain informal vocabulary. In addition, we construct suggest to construct domain sentiment vocabulary because the same word may represent different sentiments in different domains. Feature vectors are extracted from the sentiment vocabulary information and classified by Support Vector Machine(SVM). Our proposed method shows good performance in classification accuracy.

• Journal of the Institute of Electronics Engineers of Korea CI
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• v.37 no.3
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• pp.1-11
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• 2000

An example-based machine translation approach is a new paradigm for resolving various problems caused by the rules of conventional rule-based machine translation. But, in pure example-based machine translation, it is very hard to find similar examples matched with input sentences by using reasonable parallel corpus. This problem causes large overheads in the process of sentence generation. This paper proposes new method of English-Korean transfer using both patterns and examples. The patterns are composed of sentence patterns and phrase patterns. Meta parts of the patterns make the example-based machine translation more practical by raising the probability to find similar examples. The use of patterns and examples can reduce the ambiguities in source language analysis and give us a high quality of MT. And experimental results with a test corpus are discussed.