• MALSORI
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• no.62
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• pp.51-68
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• 2007

Two experiments were conducted to determine the exact locus of the frequency effect in speech production. Experiment 1 addressed the question as to whether the word frequency effect arise from the stage of lemma selection. A picture-word interference task was performed to test the significance of interactions between the effects of target frequency, distractor frequency and semantic relatedness. There was a significant interaction between the distractor frequency and the semantic relatedness and between the target and the distractor frequency. Experiment 2 examined whether the word frequency effect is attributed to the lexeme level which represent phonological information of words. A methodological logic applied to Experiment 2 was the same as that of Experiment 1. There was no significant interaction between the distractor frequency and the phonological relatedness. These results demonstrate that word frequency has influence on the processes involved in selecting a correct lemma corresponding to an activated lexical concept in speech production.

• Phonetics and Speech Sciences
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• v.13 no.2
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• pp.77-90
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• 2021

This study is to develop a Korean version of nonword intervention by modifying and supplementing a Rapid syllable transition treatment (ReST) and to determine its effect by applying it to children with CAS. Ultimately, the purpose of this study is to investigate whether nonword interventions are effective for nonword production ability and generalization of real words. Single-subject research using the ABA design was performed for a child aged five years and six months with diagnostic features of CAS. The nonwords used in the interventions were made suitable for the individual child. The intervention was provided in one-hour sessions, twice a week for six weeks. In all cases, performance of the treated three-syllable nonwords improved, and untreated three-syllable words, four-syllable words, and nonwords showed a generalization effect. However, the generalization of treatment effects to words was smaller than for nonwords. The nonword intervention was effective in improving the subject's speech motor programming skills. As a result, transition errors due to impaired speech motor programming were greatly reduced, and the ability to produce untreated nonwords was greatly increased. However, there was a limit to the full improvement of strongly habitable word errors, which would be expected if a more intensive and repetitive intervention schedule was provided.

• Proceedings of the Korean Society for Information Management Conference
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• 1999.08a
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• pp.9-12
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• 1999

통계적 확률이론에 근거한 포아송 모형을 색인어 선정 기반으로 활용하고자 하는 2-포아송 함수와 3-포아송 함수 및 다중 포아송 함수에 대한 단계적 발전 과정을 살펴보았다. 아울러, 2-포아송이 한국어 문헌의 색인어 선정에 유용한지 알아보기 위해 한국어 말뭉치 데이터베이스 내 문헌 50개를 실험 대상으로 단어의 장서빈도와 문헌빈도를 이용하여 z값을 산출해 보았다.

• Proceedings of the KSPS conference
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• 2002.11a
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• pp.165-168
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• 2002

This research was conducted to investigate the priming effect in Korean and English word production by Korean speakers. Picture-naming with distractors was used as experimental task. The type of target language, the type of distractor language and SOA(Stimulus Onset Asynchrony) were used as variables. Cross-linguistic priming effect and within-linguistic priming effect were mesured to investigate bilinguals' conceptual system.

• Proceedings of the Korean Information Science Society Conference
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• 2001.10a
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• pp.175-177
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• 2001

기존의 문서 클러스터링 알고리즘은 모든 문서가 각각 하나의 클러스터에만 할당되도록 설계되어 문서에 여러 개의 주제가 포함되어 있을지라도 문서는 유사도 비교에 의해 오직 하나의 플러스터에 포함된다는 단점이 있다. 본 연구에서는 이러한 문서 플러스터링 방법의 한계를 파악하기 위해 문서가 여러 개의 클러스터에 포함될 수 있는 계층적 중복 문서 클러스터링을 제안한다. 또한, 문서 클러스터링의 정확도를 높이기 위해서 불용어 제거 알고리즘을 이용해 불용어를 제거하여 클러스터링에 사용되는 키워드를 선별하고, 단어가중치 산출을 위한 TF*NHDF 공식을 제안한다.

• The Journal of the Korea Contents Association
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• v.16 no.11
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• pp.72-82
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• 2016

Various studies have been done in medical service area but they have just focused on the examination of the relationships between cause and effect variables. This study, thus, empirically analyzed qualitative data regarding medical service problems using word cloud technique. The major results of the paper are as follows. The data reveal ten sources in medical service - forced treatment, excess inspection, misdiagnosis, carelessness, inexperienced service, waiting for emergency, reservation problem, unkindness, process problem, and inconvenience. Major words in the category of irrecoverable service failure are misdiagnosis, careless treatment, and inexperienced service whereas those in recoverable service failure are unkind attitude and negative experience in reservation system. Those who experienced a medical service problem are usually engaged in a public act and they make public protests and legal action against very severe problems. The conclusion of this study also suggests a summary, implication, and agenda of the research.

• Spatial Information Research
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• v.23 no.2
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• pp.83-93
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• 2015

U-Services, which are offered from local governments based on their Ubiquitous City Plans, are only focused on facility and urban management services. Also Citizen oriented U-service is only planned. This study's purpose is to propose the implication for provide of the Citizen oriented U-service comparing with U-Service plan of 'Ubiquitous City Comprehensive Plan' and 'Ubiquitous City Plan' through a network text analysis and word frequency analysis. It was calculated a important keyword that was extracted the service plan contents of the 'Ubiquitous City Comprehensive Plan' and 'Ubiquitous City Plan' of the four local governments. The network text analysis and keyword frequency analysis was performed through derived keyword. Based on the analysis results, awareness of the citizens can be expected to increase about U-City by activating a excavation of Citizen oriented U-service in a variety of sector through additional services and policy of financial support in the next Ubiquitous City Comprehensive Plan.

• Korean Journal of Cognitive Science
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• v.15 no.2
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• pp.23-31
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• 2004

Latent Semantic Analysis (LSA Landauer ＆ Dumais, 1997) is a technique to represent the meanings of words using co-occurrence information of words appearing in he same context, which is usually a sentence or a document. In LSA, a word is represented as a point in multidimensional space where each axis represents a context, and a word's meaning is determined by its frequency in each context. The space is reduced by singular value decomposition (SVD). The present study elaborates upon LSA for use of representation of ambiguous words. The proposed LSA applies rotation of axes in the document space which makes possible to interpret the meaning of un. A simulation study was conducted to illustrate the performance of LSA in representation of ambiguous words. In the simulation, first, the texts which contain an ambiguous word were extracted and LSA with rotation was performed. By comparing loading matrix, we categorized the texts according to meanings. The first meaning of an ambiguous wold was represented by LSA with the matrix excluding the vectors for the other meaning. The other meanings were also represented in the same way. The simulation showed that this way of representation of an ambiguous word can identify the meanings of the word. This result suggest that LSA with axis rotation can be applied to representation of ambiguous words. We discussed that the use of rotation makes it possible to represent multiple meanings of ambiguous words, and this technique can be applied in the area of web searching.

• KIPS Transactions on Software and Data Engineering
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• v.7 no.12
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• pp.469-476
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• 2018

In order to jointly utilize research infrastructure and to build efficient construction, which are essential in science and technology research and development process. Although various classification methods have been introduced for efficient utilization of registered information, functions that can be directly utilized such as similar research infrastructure search is not yet been implemented due to limitations of collection information. In this study, we analyzed the similar search technique so far, presented the methodology for the calculation of similarity of research infrastructure, and analyzed the learning result. Study suggested that a technique can be use to extract meaningful keywords from information and analyze the similarity between the research infrastructure.

• Journal of Intelligence and Information Systems
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• v.29 no.3
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• pp.267-286
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• 2023

The conversational agents such as AI speakers utilize voice conversation for human-computer interaction. Voice recognition errors often occur in conversational situations. Recognition errors in user utterance records can be categorized into two types. The first type is misrecognition errors, where the agent fails to recognize the user's speech entirely. The second type is misinterpretation errors, where the user's speech is recognized and services are provided, but the interpretation differs from the user's intention. Among these, misinterpretation errors require separate error detection as they are recorded as successful service interactions. In this study, various text separation methods were applied to detect misinterpretation. For each of these text separation methods, the similarity of consecutive speech pairs using word embedding and document embedding techniques, which convert words and documents into vectors. This approach goes beyond simple word-based similarity calculation to explore a new method for detecting misinterpretation errors. The research method involved utilizing real user utterance records to train and develop a detection model by applying patterns of misinterpretation error causes. The results revealed that the most significant analysis result was obtained through initial consonant extraction for detecting misinterpretation errors caused by the use of unregistered neologisms. Through comparison with other separation methods, different error types could be observed. This study has two main implications. First, for misinterpretation errors that are difficult to detect due to lack of recognition, the study proposed diverse text separation methods and found a novel method that improved performance remarkably. Second, if this is applied to conversational agents or voice recognition services requiring neologism detection, patterns of errors occurring from the voice recognition stage can be specified. The study proposed and verified that even if not categorized as errors, services can be provided according to user-desired results.