• English Language & Literature Teaching
• /
• v.12 no.4
• /
• pp.69-89
• /
• 2006

This study investigated whether and how semantic nature of intransitive verbs can be related to the L2 overpassivization errors. A total of 126 Korean high school students participated in a grammaticality judgment test on English sentences in which seven semantically different types of intransitive verbs were passivized. The results showed that there was an effect of semantic type on the students' judgment on overpassivization errors. Overall, it was shown that the students experienced the lowest degree of difficulty with the Controlled Process-Motional type verbs while experiencing the high degree of difficulty with the Change of State, Existence of State, Continuation of Pre-existing State, and Uncontrolled Process types. Two interlanguage patterns were also identified: the students at higher proficiency level and those at lower-proficiency level showed distinctive patterns on the task. It was argued that the simple dichotomy of unaccusative-unergative distinction does not suffice for the explanation of the complex phenomenon of L2 overpassivization.

• Journal of the Korean Society of Industry Convergence
• /
• v.26 no.3
• /
• pp.443-454
• /
• 2023

The purpose of this study is to reveal the Korean learners' usage pattern of '의', the genitive particle, according to semantic classification, so that it can be referred to in determining the contents and methods of related education. The method of this study adopts a quantitative analysis using learners corpus established by National Institute of Korean Language. As a result of the analysis, as proficiency increases, the overall frequency of '의' increases and the number of meaning senses used increases. However, the frequency of errors also increases with it. As for the usage pattern of each sense, the meaning of 'ownership, belonging' is the most frequent, and followed by 'acting entity', 'kinship, social relations', and 'relationship(area)'. In conclusion, the meanings of 'acting subjects' and 'relationships(area) need to be supplemented with explicit education. Other meanings need to be discussed, and decisions should be made in consideration of learning purpose and proficiency.

• Journal of the Korean Institute of Telematics and Electronics C
• /
• v.34C no.5
• /
• pp.55-65
• /
• 1997

In many cases, a dialogue system can't extract the correct analysis information of a user's spoken utterance, because of its own ungrammatical components. Therefore, in order to perform a correct before it performs the syntactic processing. In this paper, we use a real dialogue corpus and classify these ungrammatical errors as 4 categories : phonological, syntactic, semantic errors that consist of speech reparis and inversions, and propose an algorithm to detect and correct the errors. In short, this paper proposes a method to detect and correct the speech repairs and inversions that are classified as the phonological and syntactic errors to implement a robust dialogue system. And, through the test of real dialogue data, this paper shows an efficiency of the proposed algorithm.

• Proceedings of the KSPS conference
• /
• 2003.10a
• /
• pp.153-156
• /
• 2003

Voice input is often required in many new application environments such as telephone-based information retrieval, car navigation systems, and user-friendly interfaces, but the low success rate of speech recognition makes it difficult to extend its application to new fields. Popular approaches to increase the accuracy of the recognition rate have been researched by post-processing of the recognition results, but previous approaches were mainly lexical-oriented ones in post error correction. We suggest a new semantic-oriented approach to correct both semantic level and lexical errors, which is also more accurate for especially domain-specific speech error correction. Through extensive experiments using a speech-driven in-vehicle telematics information application, we demonstrate the superior performance of our approach and some advantages over previous lexical-oriented approaches.

• Proceedings of the KIEE Conference
• /
• 2001.07d
• /
• pp.2610-2612
• /
• 2001

This study examines the recognition of the user's sound command based on speech recognition and natural language processing, and develops the natural language interface agent which can analyze the recognized command. The natural language interface agent consists of speech recognizer and semantic interpreter. Speech recognizer understands speech command and transforms the command into character strings. Semantic interpreter analyzes the character strings and creates the commands and questions to be transferred into the application program. We also consider the problems, related to the speech recognizer and the semantic interpreter, such as the ambiguity of natural language and the ambiguity and the errors from speech recognizer. This kind of natural language interface agent can be applied to the telephony environment involving all kind of communication media such as telephone, fax, e-mail, and so on.

• The KIPS Transactions:PartD
• /
• v.13D no.2 s.105
• /
• pp.223-234
• /
• 2006

Branching and merging have been being the outstanding methods for SCM in terms of supporting parallel developments. Since well-known commercial merging tools based on textual merging have not detecting semantics conflicts, they can cause semantic errors in the result of merging. Although a lot of researches for detecting semantic conflict and merging up to recently, these researches have been doing individually. Therefore, it is necessary for a research detecting semantic conflict on textual merging and solving it. In this paper, we propose a new method for merging which preserve semantics on textual merging. The method merging two revisions from a source program is as follows : 1) defining changing operations, which include Update, Delete, and Insert operation, per line on two revisions corresponding to the line in source program, 2) detecting textual conflicts and semantic conflict in terms of executional behaviors, 3) solving these conflicts before merging. So, the proposed method can be regarded as a hybrid method that combines a method of textual merging and a behavioral semantic merging.

• The KIPS Transactions:PartB
• /
• v.16B no.2
• /
• pp.173-180
• /
• 2009

The purpose of developing an automated scoring system for English composition is to score English writing tests and to give diagnostic feedback to the test-takers without human's efforts. The system developed through our research detects grammatical errors of a single sentence on morphological, syntactic and semantic stages, respectively, and those errors are calculated into the final score. The error detecting stages are independent from one another, which causes duplicating the identical errors with different labels at different stages. These duplicated errors become a hindering factor to calculating an accurate score. This paper presents a solution to detecting the duplicated errors and improving an accuracy in calculating the final score by eliminating one of the errors.

• IE interfaces
• /
• v.24 no.3
• /
• pp.248-257
• /
• 2011

The amount of Meta-data to be managed increases with development of information technology. However, when trying to integrate and share product information of heterogeneous systems within or between companies, sharing of information is impossible if product information classification systems are different. Due to the situation mentioned above, engineers judge the product information classification system and maps corresponding Meta-data for document-based sharing. Judging exponentially increasing amount of data by engineers and sharing product information using documents create great amount of time delay and errors in data handling. Therefore, construction of a system for integrated management and interoperability between product information based on semantic information similar to engineer's judgment is required. This paper proposes a methodology and necessity of a system for interoperability of product information based on semantic web, and also designs a system to integrate heterogeneous systems with different product information using rule based reasoning. This paper also suggests a system base for interoperability and integration of product information between heterogeneous systems by integrating the product information classification system semantically.

• KSII Transactions on Internet and Information Systems (TIIS)
• /
• v.16 no.1
• /
• pp.60-79
• /
• 2022

The U-Net architecture-based segmentation models attained remarkable performance in numerous medical image segmentation missions like skin lesion segmentation. Nevertheless, the resolution gradually decreases and the loss of spatial information increases with deeper network. The fusion of adjacent layers is not enough to make up for the lost spatial information, thus resulting in errors of segmentation boundary so as to decline the accuracy of segmentation. To tackle the issue, we propose a new deep learning-based segmentation model. In the decoding stage, the feature channels of each decoding unit are concatenated with all the feature channels of the upper coding unit. Which is done in order to ensure the segmentation effect by integrating spatial and semantic information, and promotes the robustness and generalization of our model by combining the atrous spatial pyramid pooling (ASPP) module and channel attention module (CAM). Extensive experiments on ISIC2016 and ISIC2017 common datasets proved that our model implements well and outperforms compared segmentation models for skin lesion segmentation.

• Journal of the Korean Society of Industry Convergence
• /
• v.26 no.3
• /
• pp.433-442
• /
• 2023

The purpose of this study is to reveal the Korean learners' usage pattern of '의', the genitive particle, according to semantic classification, so that it can be referred to in determining the contents and methods of related education. The method of this study adopts a quantitative analysis using learners corpus established by National Institute of Korean Language. As a result of the analysis, as proficiency increases, the overall frequency of '의' increases and the number of meaning senses used increases. However, the frequency of errors also increases with it. As for the usage pattern of each sense, the meaning of 'ownership, belonging' is the most frequent, and followed by 'acting entity', 'kinship, social relations', and 'relationship(area)'. In conclusion, the meanings of 'acting subjects' and 'relationships(area) need to be supplemented with explicit education. Other meanings need to be discussed, and decisions should be made in consideration of learning purpose and proficiency.